DBMS > Ignite vs. Memgraph vs. Riak TS vs. RocksDB vs. SiteWhere

System Properties Comparison Ignite vs. Memgraph vs. Riak TS vs. RocksDB vs. SiteWhere

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.

An open source graph database built for real-time streaming and compatible with Neo4j

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

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

M2M integration platform for persisting/querying time series data

Primary database model

Key-value store
Relational DBMS

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

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

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

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

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

ignite.apache.org

memgraph.com

rocksdb.org

github.com/sitewhere/sitewhere

Technical documentation

apacheignite.readme.io/docs

memgraph.com/docs

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

github.com/facebook/rocksdb/wiki

sitewhere1.sitewhere.io/index.html

Social network pages

Developer

Apache Software Foundation

Memgraph Ltd

Open Source, formerly Basho Technologies

Facebook, Inc.

SiteWhere

Initial release

2015

2017

2015

2013

2010

Current release

Apache Ignite 2.6

3.0.0, September 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSL 1.1; commercial license for enterprise edition available

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Erlang

C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux

Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free and schema-optional

schema-free

predefined scheme

Typing

predefined data types such as float or date

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

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

Bolt protocol
Cypher query language

HTTP API
Native Erlang Interface

C++ API
Java API

HTTP REST

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

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

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

dynamic graph partitioning

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication using RAFT

selectable replication factor

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate 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

with snapshot isolation

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Users, roles and permissions

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
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