DBMS > FoundationDB vs. Ignite vs. RocksDB vs. TimescaleDB vs. ToroDB

System Properties Comparison FoundationDB vs. Ignite vs. RocksDB vs. TimescaleDB vs. ToroDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Ordered key-value store. Core features are complimented by layers.

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.

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store
Relational DBMS

Key-value store

Time Series DBMS

Document store

Secondary database models

Relational DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

github.com/apple/foundationdb

ignite.apache.org

rocksdb.org

www.timescale.com

github.com/torodb/server

Technical documentation

apple.github.io/foundationdb

apacheignite.readme.io/docs

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

FoundationDB

Apache Software Foundation

Facebook, Inc.

Timescale

8Kdata

Initial release

2013

2015

2013

2017

2016

Current release

6.2.28, November 2020

Apache Ignite 2.6

8.11.4, April 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache 2.0

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, .Net

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

schema-free

some layers support schemas

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

some layers support typing

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

yes

string, integer, double, boolean, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

C++ API
Java API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

in SQL-layer only

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

Source-replica replication with hot standby and reads on replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Access rights for users and roles

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