DBMS > Ignite vs. JanusGraph vs. KeyDB vs. Riak TS

System Properties Comparison Ignite vs. JanusGraph vs. KeyDB vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

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.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Key-value store

Time Series DBMS

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

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

ignite.apache.org

janusgraph.org

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

apacheignite.readme.io/docs

docs.janusgraph.org

docs.keydb.dev

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Linux Foundation; originally developed as Titan by Aurelius

EQ Alpha Technology Ltd.

Open Source, formerly Basho Technologies

Initial release

2015

2017

2019

2015

Current release

Apache Ignite 2.6

0.6.3, February 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java, .Net

Java

C++

Erlang

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

restricted

SQL

Support of SQL

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

yes, limited

APIs and other access methods

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

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP API
Native Erlang Interface

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

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

yes

Lua

Erlang

Triggers

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between datasets can be stored

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

User authentification and security via Rexster Graph Server

simple password-based access control and ACL

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