DBMS > CockroachDB vs. EJDB vs. FatDB vs. Ignite

System Properties Comparison CockroachDB vs. EJDB vs. FatDB vs. Ignite

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Relational DBMS

Document store

Document store
Key-value store

Key-value store
Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

www.cockroachlabs.com

github.com/Softmotions/ejdb

ignite.apache.org

Technical documentation

www.cockroachlabs.com/docs

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

apacheignite.readme.io/docs

Developer

Cockroach Labs

Softmotions

FatCloud

Apache Software Foundation

Initial release

2015

2012

2015

Current release

23.1.1, May 2023

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java, .Net

Server operating systems

Linux
macOS
Windows

server-less

Windows

Linux
OS X
Solaris
Windows

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

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

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

via applications

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

via applications

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

none

selectable replication factor

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

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

Role-based access control

Can implement custom security layer via applications

Security Hooks for custom implementations

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More resources

Recent citations in the news

Cockroach Labs Deepens Partnership with Google Cloud, CockroachDB Selected to Join Google Distributed Cloud
9 April 2024, PR Newswire

CockroachDB tempts legacy databases to crawl into the cloud age
29 January 2024, The Register

How DoorDash Migrated from Aurora Postgres to CockroachDB
5 December 2023, The New Stack

How to Unlock Real-Time Data Streams with CockroachDB and Amazon MSK | Amazon Web Services
6 November 2023, AWS Blog

DoorDash Uses CockroachDB to Create Config Management Platform for Microservices
14 February 2024, InfoQ.com

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

provided by Google News

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