DBMS > EJDB vs. etcd vs. RocksDB

System Properties Comparison EJDB vs. etcd vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A distributed reliable key-value store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Key-value store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

github.com/Softmotions/ejdb

etcd.io
github.com/etcd-io/etcd

rocksdb.org

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/facebook/rocksdb/wiki

Developer

Softmotions

Facebook, Inc.

Initial release

2012

2013

Current release

3.4, August 2019

8.11.4, April 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Server operating systems

server-less

FreeBSD
Linux
Windows

experimental

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

SQL

Support of SQL

APIs and other access methods

in-process shared library

gRPC
JSON over HTTP

C++ API
Java API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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