NOTE: Issues tracker is disabled. You are welcome to contribute, pull requests accepted.

EJDB2 is an embeddable JSON database engine published under MIT license.

The Story of the IT-depression, birds and EJDB 2.0

• C11 API
• Single file database
• Online backups support
• 500K library size for Android
• iOS / Android / React Native / Flutter integration
• Simple but powerful query language (JQL) as well as support of the following standards:
  • rfc6902 JSON Patch
  • rfc7386 JSON Merge patch
  • rfc6901 JSON Path
• Support of collection joins
• Powered by iowow.io - The persistent key/value storage engine
• HTTP REST/Websockets endpoints powered by IWNET and BearSSL.
• JSON documents are stored in using fast and compact binn binary format

• Native language bindings
• Supported platforms
  • macOS
  • iOS
  • Linux
  • Android
  • Windows
• JQL query language
  • Grammar
  • Quick into
  • Data modification
  • Projections
  • Collection joins
  • Sorting
  • Query options
• Indexes and performance
• Network API
  • HTTP API
  • Websockets API
• C API
• License

[1] No HTTP/Websocket support #257
[2] Binaries are not distributed with dart pub. You can build it manually
[3] Can be build, but needed a linkage with windows node/dart libs.
[4] Porting in progress #273

• NodeJS
• Dart
• Java
• Android support
• Swift | iOS
• React Native
• Flutter

• Go
  • https://github.com/memmaker/go-ejdb2
• Rust
  • https://crates.io/crates/ejdb2
• .Net
  • https://github.com/kmvi/ejdb2-csharp
• Haskell
  • https://github.com/cescobaz/ejdb2haskell
  • https://hackage.haskell.org/package/ejdb2-binding
• Pharo
  • https://github.com/pharo-nosql/pharo-ejdb
• Lua
  • https://github.com/chriku/ejdb-lua

• EJDB 2.0 core engine is well tested and used in various heavily loaded deployments
• Tested on Linux, macOS and FreeBSD. Has limited Windows support
• Old EJDB 1.x version can be found in separate ejdb_1.x branch. We are not maintaining ejdb 1.x.

• Wirow video conferencing platform

Are you using EJDB? Let me know!

EJDB2 code ported and tested on High Sierra / Mojave / Catalina

EJDB2 Swift binding for MacOS, iOS and Linux. Swift binding is outdated at now. Looking for contributors.

brew install ejdb

cmake v3.24 or higher required

git clone --recurse-submodules [email protected]:Softmotions/ejdb.git

mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make install

mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DPACKAGE_DEB=ON
make package

mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DPACKAGE_RPM=ON
make package

EJDB2 can be cross-compiled for windows

Note: HTTP/Websocket network API is disabled and not yet supported

Nodejs/Dart bindings not yet ported to Windows.

Cross-compilation Guide for Windows

IWSTART is an automatic CMake initial project generator for C projects based on iowow / iwnet / ejdb2 libs.

https://github.com/Softmotions/iwstart

• Flutter binding
• React Native binding

• https://github.com/Softmotions/ejdb/tree/master/src/bindings/ejdb2_android/test

• https://github.com/Softmotions/ejdb_android_todo_app

EJDB query language (JQL) syntax inspired by ideas behind XPath and Unix shell pipes. It designed for easy querying and updating sets of JSON documents.

JQL parser created created by peg/leg — recursive-descent parser generators for C Here is the formal parser grammar: https://github.com/Softmotions/ejdb/blob/master/src/jql/jqp.leg

Notation used below is based on SQL syntax description:

QUERY = FILTERS [ '|' APPLY ] [ '|' PROJECTIONS ] [ '|' OPTS ];

STR = { quoted_string | unquoted_string };

JSONVAL = json_value;

PLACEHOLDER = { ':'placeholder_name | '?' }

FILTERS = FILTER [{ and | or } [ not ] FILTER];

  FILTER = [@collection_name]/NODE[/NODE]...;

  NODE = { '*' | '**' | NODE_EXPRESSION | STR };

  NODE_EXPRESSION = '[' NODE_EXPR_LEFT OP NODE_EXPR_RIGHT ']'
                        [{ and | or } [ not ] NODE_EXPRESSION]...;

  OP =   [ '!' ] { '=' | '>=' | '<=' | '>' | '<' | ~ }
      | [ '!' ] { 'eq' | 'gte' | 'lte' | 'gt' | 'lt' }
      | [ not ] { 'in' | 'ni' | 're' };

  NODE_EXPR_LEFT = { '*' | '**' | STR | NODE_KEY_EXPR };

  NODE_KEY_EXPR = '[' '*' OP NODE_EXPR_RIGHT ']'

  NODE_EXPR_RIGHT =  JSONVAL | STR | PLACEHOLDER

APPLY = { 'apply' | 'upsert' } { PLACEHOLDER | json_object | json_array  } | 'del'

OPTS = { 'skip' n | 'limit' n | 'count' | 'noidx' | 'inverse' | ORDERBY }...

  ORDERBY = { 'asc' | 'desc' } PLACEHOLDER | json_path

PROJECTIONS = PROJECTION [ {'+' | '-'} PROJECTION ]

  PROJECTION = 'all' | json_path

• json_value: Any valid JSON value: object, array, string, bool, number.
• json_path: Simplified JSON pointer. Eg.: /foo/bar or /foo/"bar with spaces"/
• * in context of NODE: Any JSON object key name at particular nesting level.
• ** in context of NODE: Any JSON object key name at arbitrary nesting level.
• * in context of NODE_EXPR_LEFT: Key name at specific level.
• ** in context of NODE_EXPR_LEFT: Nested array value of array element under specific key.

Lets play with some very basic data and queries. For simplicity we will use ejdb websocket network API which provides us a kind of interactive CLI. The same job can be done using pure C API too (ejdb2.h jql.h).

NOTE: Take a look into JQL test cases for more examples.

{
  "firstName": "John",
  "lastName": "Doe",
  "age": 28,
  "pets": [
    {"name": "Rexy rex", "kind": "dog", "likes": ["bones", "jumping", "toys"]},
    {"name": "Grenny", "kind": "parrot", "likes": ["green color", "night", "toys"]}
  ]
}

Save json as sample.json then upload it the family collection:

# Start HTTP/WS server protected by some access token
./jbs -a 'myaccess01'
8 Mar 16:15:58.601 INFO: HTTP/WS endpoint at localhost:9191

Server can be accessed using HTTP or Websocket endpoint. More info

curl -d '@sample.json' -H'X-Access-Token:myaccess01' -X POST http://localhost:9191/family

We can play around using interactive wscat websocket client.

wscat  -H 'X-Access-Token:myaccess01' -c http://localhost:9191
connected (press CTRL+C to quit)
> k info
< k     {
 "version": "2.0.0",
 "file": "db.jb",
 "size": 8192,
 "collections": [
  {
   "name": "family",
   "dbid": 3,
   "rnum": 1,
   "indexes": []
  }
 ]
}

> k get family 1
< k     1       {
 "firstName": "John",
 "lastName": "Doe",
 "age": 28,
 "pets": [
  {
   "name": "Rexy rex",
   "kind": "dog",
   "likes": [
    "bones",
    "jumping",
    "toys"
   ]
  },
  {
   "name": "Grenny",
   "kind": "parrot",
   "likes": [
    "green color",
    "night",
    "toys"
   ]
  }
 ]
}

Note about the k prefix before every command; It is an arbitrary key chosen by client and designated to identify particular websocket request, this key will be returned with response to request and allows client to identify that response for his particular request. More info

Query command over websocket has the following format:

<key> query <collection> <query>

So we will consider only <query> part in this document.

k query family /*

or

k query family /**

or specify collection name in query explicitly

k @family/*

We can execute query by HTTP POST request

curl --data-raw '@family/[firstName = John]' -H'X-Access-Token:myaccess01' -X POST http://localhost:9191

1	{"firstName":"John","lastName":"Doe","age":28,"pets":[{"name":"Rexy rex","kind":"dog","likes":["bones","jumping","toys"]},{"name":"Grenny","kind":"parrot","likes":["green color","night","toys"]}]}

k @family/* | limit 10

Element at index 1 exists in likes array within a pets sub-object

> k query family /pets/*/likes/1
< k     1       {"firstName":"John"...

Element at index 1 exists in likes array at any likes nesting level

> k query family /**/likes/1
< k     1       {"firstName":"John"...

From this point and below I will omit websocket specific prefix k query family and consider only JQL queries.

In order to get documents by primary key the following options are available:

1. Use API call ejdb_get()

    const doc = await db.get('users', 112);

2. Use the special query construction: /=:? or @collection/=:?

Get document from users collection with primary key 112

> k @users/=112

Update tags array for document in jobs collection (TypeScript):

 await db.createQuery('@jobs/ = :? | apply :? | count')
    .setNumber(0, id)
    .setJSON(1, { tags })
    .completionPromise();

Array of primary keys can also be used for matching:

 await db.createQuery('@jobs/ = :?| apply :? | count')
    .setJSON(0, [23, 1, 2])
    .setJSON(1, { tags })
    .completionPromise();

Below is a set of self explaining queries:

/pets/*/[name = "Rexy rex"]

/pets/*/[name eq "Rexy rex"]

/pets/*/[name = "Rexy rex" or name = Grenny]

Note about quotes around words with spaces.

Get all documents where owner age greater than 20 and have some pet who like bones or toys

/[age > 20] and /pets/*/likes/[** in ["bones", "toys"]]

Here ** denotes some element in likes array.

ni is the inverse operator to in. Get documents where bones somewhere in likes array.

/pets/*/[likes ni "bones"]

We can create more complicated filters

( /[age <= 20] or /[lastName re "Do.*"] )
  and /pets/*/likes/[** in ["bones", "toys"]]

Note about grouping parentheses and regular expression matching using re operator.

~ is a prefix matching operator (Since ejdb v2.0.53). Prefix matching can benefit from using indexes.

Get documents where /lastName starts with "Do".

/[lastName ~ Do]

Filter documents with likes array exactly matched to ["bones","jumping","toys"]

/**/[likes = ["bones","jumping","toys"]]

Matching algorithms for arrays and maps are different:

• Array elements are matched from start to end. In equal arrays all values at the same index should be equal.
• Object maps matching consists of the following steps:
  • Lexicographically sort object keys in both maps.
  • Do matching keys and its values starting from the lowest key.
  • If all corresponding keys and values in one map are fully matched to ones in other and vice versa, maps considered to be equal. For example: {"f":"d","e":"j"} and {"e":"j","f":"d"} are equal maps.

Find JSON document having firstName key at root level.

/[* = "firstName"]

I this context * denotes a key name.

You can use conditions on key name and key value at the same time:

/[[* = "firstName"] = John]

Key name can be either firstName or lastName but should have John value in any case.

/[[* in ["firstName", "lastName"]] = John]

It may be useful in queries with dynamic placeholders (C API):

/[[* = :keyName] = :keyValue]

APPLY section responsible for modification of documents content.

APPLY = ({'apply' | `upsert`} { PLACEHOLDER | json_object | json_array  }) | 'del'

JSON patch specs conformed to rfc7386 or rfc6902 specifications followed after apply keyword.

Let's add address object to all matched document

/[firstName = John] | apply {"address":{"city":"New York", "street":""}}

If JSON object is an argument of apply section it will be treated as merge match (rfc7386) otherwise it should be array which denotes rfc6902 JSON patch. Placeholders also supported by apply section.

/* | apply :?

Set the street name in address

/[firstName = John] | apply [{"op":"replace", "path":"/address/street", "value":"Fifth Avenue"}]

Add Neo fish to the set of John's pets

/[firstName = John]
| apply [{"op":"add", "path":"/pets/-", "value": {"name":"Neo", "kind":"fish"}}]

upsert updates existing document by given json argument used as merge patch or inserts provided json argument as new document instance.

/[firstName = John] | upsert {"firstName": "John", "address":{"city":"New York"}}

Increments numeric value identified by JSON path by specified value.

Example:

 Document:  {"foo": 1}
 Patch:     [{"op": "increment", "path": "/foo", "value": 2}]
 Result:    {"foo": 3}

Same as JSON patch add but creates intermediate object nodes for missing JSON path segments.

Example:

Document: {"foo": {"bar": 1}}
Patch:    [{"op": "add_create", "path": "/foo/zaz/gaz", "value": 22}]
Result:   {"foo":{"bar":1,"zaz":{"gaz":22}}}

Example:

Document: {"foo": {"bar": 1}}
Patch:    [{"op": "add_create", "path": "/foo/bar/gaz", "value": 22}]
Result:   Error since element pointed by /foo/bar is not an object

Swaps two values of JSON document starting from from path.

Swapping rules

1. If value pointed by from not exists error will be raised.
2. If value pointed by path not exists it will be set by value from from path, then object pointed by from path will be removed.
3. If both values pointed by from and path are presented they will be swapped.

Example:

Document: {"foo": ["bar"], "baz": {"gaz": 11}}
Patch:    [{"op": "swap", "from": "/foo/0", "path": "/baz/gaz"}]
Result:   {"foo": [11], "baz": {"gaz": "bar"}}

Example (Demo of rule 2):

Document: {"foo": ["bar"], "baz": {"gaz": 11}}
Patch:    [{"op": "swap", "from": "/foo/0", "path": "/baz/zaz"}]
Result:   {"foo":[],"baz":{"gaz":11,"zaz":"bar"}}

Use del keyword to remove matched elements from collection:

/FILTERS | del

Example:

> k add family {"firstName":"Jack"}
< k     2
> k query family /[firstName re "Ja.*"]
< k     2       {"firstName":"Jack"}

# Remove selected elements from collection
> k query family /[firstName=Jack] | del
< k     2       {"firstName":"Jack"}

PROJECTIONS = PROJECTION [ {'+' | '-'} PROJECTION ]

  PROJECTION = 'all' | json_path | join_clause

Projection allows to get only subset of JSON document excluding not needed data.

Query placeholders API is supported in projections.

Lets add one more document to our collection:

$ cat << EOF | curl -d @- -H'X-Access-Token:myaccess01' -X POST http://localhost:9191/family
{
"firstName":"Jack",
"lastName":"Parker",
"age":35,
"pets":[{"name":"Sonic", "kind":"mouse", "likes":[]}]
}
EOF

Now query only pet owners firstName and lastName from collection.

> k query family /* | /{firstName,lastName}

< k     3       {"firstName":"Jack","lastName":"Parker"}
< k     1       {"firstName":"John","lastName":"Doe"}
< k

Add pets array for every document

> k query family /* | /{firstName,lastName} + /pets

< k     3       {"firstName":"Jack","lastName":"Parker","pets":[...
< k     1       {"firstName":"John","lastName":"Doe","pets":[...

Exclude only pets field from documents

> k query family /* | all - /pets

< k     3       {"firstName":"Jack","lastName":"Parker","age":35}
< k     1       {"firstName":"John","lastName":"Doe","age":28,"address":{"city":"New York","street":"Fifth Avenue"}}
< k

Here all keyword used denoting whole document.

Get age and the first pet in pets array.

> k query family /[age > 20] | /age + /pets/0

< k     3       {"age":35,"pets":[{"name":"Sonic","kind":"mouse","likes":[]}]}
< k     1       {"age":28,"pets":[{"name":"Rexy rex","kind":"dog","likes":["bones","jumping","toys"]}]}
< k

Join materializes reference to document to a real document objects which will replace reference inplace.

Documents are joined by their primary keys only.

Reference keys should be stored in referrer document as number or string field.

Joins can be specified as part of projection expression in the following form:

/.../field<collection

Where

• field ‐ JSON field contains primary key of joined document.
• < ‐ The special mark symbol which instructs EJDB engine to replace field key by body of joined document.
• collection ‐ name of DB collection where joined documents located.

A referrer document will be untouched if associated document is not found.

Here is the simple demonstration of collection joins in our interactive websocket shell:

> k add artists {"name":"Leonardo Da Vinci", "years":[1452,1519]}
< k     1
> k add paintings {"name":"Mona Lisa", "year":1490, "origin":"Italy", "artist": 1}
< k     1
> k add paintings {"name":"Madonna Litta - Madonna And The Child", "year":1490, "origin":"Italy", "artist": 1}
< k     2

# Lists paintings documents

> k @paintings/*
< k     2       {"name":"Madonna Litta - Madonna And The Child","year":1490,"origin":"Italy","artist":1}
< k     1       {"name":"Mona Lisa","year":1490,"origin":"Italy","artist":1}
< k
>

# Do simple join with artists collection

> k @paintings/* | /artist<artists
< k     2       {"name":"Madonna Litta - Madonna And The Child","year":1490,"origin":"Italy",
                  "artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}

< k     1       {"name":"Mona Lisa","year":1490,"origin":"Italy",
                  "artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k


# Strip all document fields except `name` and `artist` join

> k @paintings/* | /artist<artists + /name + /artist/*
< k     2       {"name":"Madonna Litta - Madonna And The Child","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k     1       {"name":"Mona Lisa","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k
>

# Same results as above:

> k @paintings/* | /{name, artist<artists} + /artist/*
< k     2       {"name":"Madonna Litta - Madonna And The Child","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k     1       {"name":"Mona Lisa","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k

Invalid references:

>  k add paintings {"name":"Mona Lisa2", "year":1490, "origin":"Italy", "artist": 9999}
< k     3
> k @paintings/* |  /artist<artists
< k     3       {"name":"Mona Lisa2","year":1490,"origin":"Italy","artist":9999}
< k     2       {"name":"Madonna Litta - Madonna And The Child","year":1490,"origin":"Italy","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}
< k     1       {"name":"Mona Lisa","year":1490,"origin":"Italy","artist":{"name":"Leonardo Da Vinci","years":[1452,1519]}}

  ORDERBY = ({ 'asc' | 'desc' } PLACEHOLDER | json_path)...

Lets add one more document then sort documents in collection according to firstName ascending and age descending order.

> k add family {"firstName":"John", "lastName":"Ryan", "age":39}
< k     4

> k query family /* | /{firstName,lastName,age} | asc /firstName desc /age
< k     3       {"firstName":"Jack","lastName":"Parker","age":35}
< k     4       {"firstName":"John","lastName":"Ryan","age":39}
< k     1       {"firstName":"John","lastName":"Doe","age":28}
< k

asc, desc instructions may use indexes defined for collection to avoid a separate documents sorting stage.

OPTS = { 'skip' n | 'limit' n | 'count' | 'noidx' | 'inverse' | ORDERBY }...

• skip n Skip first n records before first element in result set
• limit n Set max number of documents in result set
• count Returns only count of matched documents

  > k query family /* | count
  < k     3
  < k
  

• noidx Do not use any indexes for query execution.
• inverse By default query scans documents from most recently added to older ones. This option inverts scan direction to opposite and activates noidx mode. Has no effect if query has asc/desc sorting clauses.

Database index can be build for any JSON field path containing values of number or string type. Index can be an unique ‐ not allowing value duplication and non unique. The following index mode bit mask flags are used (defined in ejdb2.h):

For example unique index of string type will be specified by EJDB_IDX_UNIQUE | EJDB_IDX_STR = 0x05. Index can be defined for only one value type located under specific path in json document.

Lets define non unique string index for /lastName path:

> k idx family 4 /lastName
< k

Index selection for queries based on set of heuristic rules.

You can always check index usage by issuing explain command in WS API:

> k explain family /[lastName=Doe] and /[age!=27]
< k     explain [INDEX] MATCHED  STR|3 /lastName EXPR1: 'lastName = Doe' INIT: IWKV_CURSOR_EQ
[INDEX] SELECTED STR|3 /lastName EXPR1: 'lastName = Doe' INIT: IWKV_CURSOR_EQ
 [COLLECTOR] PLAIN

The following statements are taken into account when using EJDB2 indexes:

• Only one index can be used for particular query execution

• If query consist of or joined part at top level or contains negated expressions at the top level of query expression - indexes will not be in use at all. So no indexes below:

  /[lastName != Andy]
  
  /[lastName = "John"] or /[lastName = Peter]
  
  

  But will be used /lastName index defined above

  /[lastName = Doe]
  
  /[lastName = Doe] and /[age = 28]
  
  /[lastName = Doe] and not /[age = 28]
  
  /[lastName = Doe] and /[age != 28]
  

• The following operators are supported by indexes (ejdb 2.0.x):

  • eq, =
  • gt, >
  • gte, >=
  • lt, <
  • lte, <=
  • in
  • ~ (Prefix matching since ejdb 2.0.53)

• ORDERBY clauses may use indexes to avoid result set sorting.

• Array fields can also be indexed. Let's outline typical use case: indexing of some entity tags:

  > k add books {"name":"Mastering Ultra", "tags":["ultra", "language", "bestseller"]}
  < k     1
  > k add books {"name":"Learn something in 24 hours", "tags":["bestseller"]}
  < k     2
  > k query books /*
  < k     2       {"name":"Learn something in 24 hours","tags":["bestseller"]}
  < k     1       {"name":"Mastering Ultra","tags":["ultra","language","bestseller"]}
  < k
  

  Create string index for /tags

  > k idx books 4 /tags
  < k
  

  Filter books by bestseller tag and show index usage in query:

  > k explain books /tags/[** in ["bestseller"]]
  < k     explain [INDEX] MATCHED  STR|4 /tags EXPR1: '** in ["bestseller"]' INIT: IWKV_CURSOR_EQ
  [INDEX] SELECTED STR|4 /tags EXPR1: '** in ["bestseller"]' INIT: IWKV_CURSOR_EQ
  [COLLECTOR] PLAIN
  
  < k     1       {"name":"Mastering Ultra","tags":["ultra","language","bestseller"]}
  < k     2       {"name":"Learn something in 24 hours","tags":["bestseller"]}
  < k
  

All documents in collection are sorted by their primary key in descending order. So if you use auto generated keys (ejdb_put_new) you may be sure what documents fetched as result of full scan query will be ordered according to the time of insertion in descendant order, unless you don't use query sorting, indexes or inverse keyword.

In many cases, using index may drop down the overall query performance. Because index collection contains only document references (id) and engine may perform an addition document fetching by its primary key to finish query matching. So for not so large collections a brute scan may perform better than scan using indexes. However, exact matching operations: eq, in and sorting by natural index order will benefit from index in most cases.

If you'd like update some set of documents with apply or del operations but don't want fetching all of them as result of query - just add count modifier to the query to get rid of unnecessary data transferring and json data conversion.

EJDB engine provides the ability to start a separate HTTP/Websocket endpoint worker exposing network API for quering and data modifications. SSL (TLS 1.2) is supported by jbs server.

The easiest way to expose database over the network is use the standalone jbs server. (Of course if you want to avoid C API integration).

Usage:

	 ./jbs [options]

	-v, --version		Print program version.
	-f, --file=<>		Database file path. Default: ejdb2.db
	-p, --port=NUM		HTTP server port numer. Default: 9191
	-l, --listen=<>		Network address server will listen. Default: localhost
	-k, --key=<>		PEM private key file for TLS 1.2 HTTP server.
	-c, --certs=<>		PEM certificates file for TLS 1.2 HTTP server.
	-a, --access=TOKEN|@FILE		Access token to match 'X-Access-Token' HTTP header value.
	-r, --access-read		Allows unrestricted read-only data access.
	-C, --cors		Enable COSR response headers for HTTP server
	-t, --trunc		Cleanup/reset database file on open.
	-w, --wal		use the write ahead log (WAL). Used to provide data durability.

Advanced options:
	-S, --sbz=NUM		Max sorting buffer size. If exceeded, an overflow temp file for data will be created.
                  Default: 16777216, min: 1048576
	-D, --dsz=NUM		Initial size of buffer to process/store document on queries. Preferable average size of document. 
                  Default: 65536, min: 16384
	-T, --trylock Exit with error if database is locked by another process. 
                If not set, current process will wait for lock release.

HTTP endpoint may be protected by a token specified with --access flag or C API EJDB_HTTP struct. If access token was set, client should provide X-Access-Token HTTP header. If token is required but not provided by client 401 HTTP code will be reported. If access token is not matched to the token provided by client server will respond with 403 HTTP code.

Add a new document to the collection.

• 200 success. Body: a new document identifier as int64 number

Replaces/store document under specific numeric id

• 200 on success. Empty body

Removes document identified by id from a collection

• 200 on success. Empty body
• 404 document not found

Patch a document identified by id by rfc7396, rfc6902 data.

• 200 on success. Empty body

Retrieve document identified by id from a collection.

• 200 on success. Body: JSON document text.
  • content-type:application/json
  • content-length:
• 404 document not found

Query a collection by provided query as POST body. Body of query should contains collection name in use in the first filter element: @collection_name/... Request headers:

• X-Hints comma separated extra hints to ejdb2 database engine.
  • explain Show query execution plan before first element in result set separated by -------------------- line. Response:
• Response data transfered using HTTP chunked transfer encoding
• 200 on success.
• JSON documents separated by \n in the following format:

  \r\n<document id>\t<document JSON body>
  ...
  

Example:

curl -v --data-raw '@family/[age > 18]' -H 'X-Access-Token:myaccess01' http://localhost:9191
* Rebuilt URL to: http://localhost:9191/
*   Trying 127.0.0.1...
* TCP_NODELAY set
* Connected to localhost (127.0.0.1) port 9191 (#0)
> POST / HTTP/1.1
> Host: localhost:9191
> User-Agent: curl/7.58.0
> Accept: */*
> X-Access-Token:myaccess01
> Content-Length: 18
> Content-Type: application/x-www-form-urlencoded
>
* upload completely sent off: 18 out of 18 bytes
< HTTP/1.1 200 OK
< connection:keep-alive
< content-type:application/json
< transfer-encoding:chunked
<

4	{"firstName":"John","lastName":"Ryan","age":39}
3	{"firstName":"Jack","lastName":"Parker","age":35,"pets":[{"name":"Sonic","kind":"mouse","likes":[]}]}
1	{"firstName":"John","lastName":"Doe","age":28,"pets":[{"name":"Rexy rex","kind":"dog","likes":["bones","jumping","toys"]},{"name":"Grenny","kind":"parrot","likes":["green color","night","toys"]}],"address":{"city":"New York","street":"Fifth Avenue"}}
* Connection #0 to host localhost left intact

curl --data-raw '@family/[lastName = "Ryan"]' -H 'X-Access-Token:myaccess01' -H 'X-Hints:explain' http://localhost:9191
[INDEX] MATCHED  STR|3 /lastName EXPR1: 'lastName = "Ryan"' INIT: IWKV_CURSOR_EQ
[INDEX] SELECTED STR|3 /lastName EXPR1: 'lastName = "Ryan"' INIT: IWKV_CURSOR_EQ
 [COLLECTOR] PLAIN
--------------------
4	{"firstName":"John","lastName":"Ryan","age":39}

Fetch ejdb JSON metadata and available HTTP methods in Allow response header. Example:

curl -X OPTIONS -H 'X-Access-Token:myaccess01'  http://localhost:9191/
{
 "version": "2.0.0",
 "file": "db.jb",
 "size": 16384,
 "collections": [
  {
   "name": "family",
   "dbid": 3,
   "rnum": 3,
   "indexes": [
    {
     "ptr": "/lastName",
     "mode": 4,
     "idbf": 64,
     "dbid": 4,
     "rnum": 3
    }
   ]
  }
 ]
}

EJDB supports simple text based protocol over HTTP websocket protocol. You can use interactive websocket CLI tool wscat to communicate with server by hands.

Will respond with the following help text message:

wscat  -H 'X-Access-Token:myaccess01' -c http://localhost:9191
> ?
<
<key> info
<key> get     <collection> <id>
<key> set     <collection> <id> <document json>
<key> add     <collection> <document json>
<key> del     <collection> <id>
<key> patch   <collection> <id> <patch json>
<key> idx     <collection> <mode> <path>
<key> rmi     <collection> <mode> <path>
<key> rmc     <collection>
<key> query   <collection> <query>
<key> explain <collection> <query>
<key> <query>
>

Note about <key> prefix before every command; It is an arbitrary key chosen by client and designated to identify particular websocket request, this key will be returned with response to request and allows client to identify that response for his particular request.

Errors are returned in the following format:

<key> ERROR: <error description>

Get database metadatas as JSON document.

Retrieve document identified by id from a collection. If document is not found IWKV_ERROR_NOTFOUND will be returned.

Example:

> k get family 3
< k     3       {
 "firstName": "Jack",
 "lastName": "Parker",
 "age": 35,
 "pets": [
  {
   "name": "Sonic",
   "kind": "mouse",
   "likes": []
  }
 ]
}

If document not found we will get error:

> k get family 55
< k ERROR: Key not found. (IWKV_ERROR_NOTFOUND)
>

Replaces/add document under specific numeric id. Collection will be created automatically if not exists.

Add new document to <collection> New id of document will be generated and returned as response. `Collection> will be created automatically if not exists.

Example:

> k add mycollection {"foo":"bar"}
< k     1
> k add mycollection {"foo":"bar"}
< k     2
>

Remove document identified by id from the collection. If document is not found IWKV_ERROR_NOTFOUND will be returned.

Apply rfc7396 or rfc6902 patch to the document identified by id. If document is not found IWKV_ERROR_NOTFOUND will be returned.

Execute query on documents in specified collection. Response: A set of WS messages with document boidies terminated by the last message with empty body.

> k query family /* | /firstName
< k     4       {"firstName":"John"}
< k     3       {"firstName":"Jack"}
< k     1       {"firstName":"John"}
< k

Note about last message: <key> with no body.

Same as <key> query <collection> <query> but the first response message will be prefixed by <key> explain and contains query execution plan.

Example:

> k explain family /* | /firstName
< k     explain [INDEX] NO [COLLECTOR] PLAIN

< k     4       {"firstName":"John"}
< k     3       {"firstName":"Jack"}
< k     1       {"firstName":"John"}
< k

Execute query text. Body of query should contains collection name in use in the first filter element: @collection_name/.... Behavior is the same as for: <key> query <collection> <query>

Ensure index with specified mode (bitmask flag) for given json path and collection. Collection will be created if not exists.

Set unique string index (0x01 & 0x04) = 5 on /name JSON field:

k idx mycollection 5 /name

Remove index with specified mode (bitmask flag) for given json path and collection. Return error if given index not found.

Remove collection and all of its data. Note: If collection is not found no errors will be reported.

If you have Docker installed, you can build a Docker image and run it in a container

cd docker
docker build -t ejdb2 .
docker run -d -p 9191:9191 --name myEJDB ejdb2 --access myAccessKey

or get an image of ejdb2 directly from the Docker Hub

docker run -d -p 9191:9191 --name myEJDB softmotions/ejdb2 --access myAccessKey

EJDB can be embedded into any C/C++ application. C API documented in the following headers:

• ejdb.h Main API functions
• jbl.h JSON documents management API
• jql.h Query building API

Example application:

#include <ejdb2/ejdb2.h>

#define CHECK(rc_)          \
  if (rc_) {                 \
    iwlog_ecode_error3(rc_); \
    return 1;                \
  }

static iwrc documents_visitor(EJDB_EXEC *ctx, const EJDB_DOC doc, int64_t *step) {
  // Print document to stderr
  return jbl_as_json(doc->raw, jbl_fstream_json_printer, stderr, JBL_PRINT_PRETTY);
}

int main() {

  EJDB_OPTS opts = {
    .kv = {
      .path = "example.db",
      .oflags = IWKV_TRUNC
    }
  };
  EJDB db;     // EJDB2 storage handle
  int64_t id;  // Document id placeholder
  JQL q = 0;   // Query instance
  JBL jbl = 0; // Json document

  iwrc rc = ejdb_init();
  CHECK(rc);

  rc = ejdb_open(&opts, &db);
  CHECK(rc);

  // First record
  rc = jbl_from_json(&jbl, "{\"name\":\"Bianca\", \"age\":4}");
  RCGO(rc, finish);
  rc = ejdb_put_new(db, "parrots", jbl, &id);
  RCGO(rc, finish);
  jbl_destroy(&jbl);

  // Second record
  rc = jbl_from_json(&jbl, "{\"name\":\"Darko\", \"age\":8}");
  RCGO(rc, finish);
  rc = ejdb_put_new(db, "parrots", jbl, &id);
  RCGO(rc, finish);
  jbl_destroy(&jbl);

  // Now execute a query
  rc =  jql_create(&q, "parrots", "/[age > :age]");
  RCGO(rc, finish);

  EJDB_EXEC ux = {
    .db = db,
    .q = q,
    .visitor = documents_visitor
  };

  // Set query placeholder value.
  // Actual query will be /[age > 3]
  rc = jql_set_i64(q, "age", 0, 3);
  RCGO(rc, finish);

  // Now execute the query
  rc = ejdb_exec(&ux);

finish:
  jql_destroy(&q);
  jbl_destroy(&jbl);
  ejdb_close(&db);
  CHECK(rc);
  return 0;
}

Compile and run:

gcc -std=gnu11 -Wall -pedantic -c -o example1.o example1.c
gcc -o example1 example1.o -lejdb2

./example1
{
 "name": "Darko",
 "age": 8
}{
 "name": "Bianca",
 "age": 4
}

MIT License

Copyright (c) 2012-2022 Softmotions Ltd <[email protected]>

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.