DBMS > IBM Db2 Event Store vs. Ignite vs. JaguarDB vs. Riak TS

System Properties Comparison IBM Db2 Event Store vs. Ignite vs. JaguarDB vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

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.

Performant, highly scalable DBMS for AI and IoT applications

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

Primary database model

Event Store
Time Series DBMS

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Time Series DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.ibm.com/products/db2-event-store

ignite.apache.org

www.jaguardb.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

apacheignite.readme.io/docs

www.jaguardb.com/support.html

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

Developer

IBM

Apache Software Foundation

DataJaguar, Inc.

Open Source, formerly Basho Technologies

Initial release

2017

2015

Current release

2.0

Apache Ignite 2.6

3.3 July 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

GPL V3.0

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 and C++

C++, Java, .Net

C++

the server part. Clients available in other languages

Erlang

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Solaris
Windows

Linux

Linux
OS X

Data scheme

yes

schema-free

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

yes

through the embedded Spark runtime

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes, limited

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
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

Server-side scripts

Stored procedures

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes (replicated cache)

Multi-source replication

selectable replication factor

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

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

rights management via user accounts

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