DBMS > Badger vs. EJDB vs. Microsoft Azure Cosmos DB vs. SWC-DB vs. TerarkDB

System Properties Comparison Badger vs. EJDB vs. Microsoft Azure Cosmos DB vs. SWC-DB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Globally distributed, horizontally scalable, multi-model database service

A high performance, scalable Wide Column DBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Key-value store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Key-value store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

azure.microsoft.com/services/cosmos-db

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/bytedance/terarkdb

Technical documentation

godoc.org/github.com/dgraph-io/badger

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

learn.microsoft.com/azure/cosmos-db

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

DGraph Labs

Softmotions

Microsoft

Alex Kashirin

ByteDance, originally Terark

Initial release

2017

2012

2014

2020

2016

Current release

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

commercial

Open Source

GPL V3

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

hosted

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON types

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

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

APIs and other access methods

in-process shared library

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Proprietary protocol
Thrift

C++ API
Java API

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++

C++
Java

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

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

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights can be defined down to the item level

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