DBMS > AgensGraph vs. IBM Db2 Event Store vs. Ignite vs. STSdb

System Properties Comparison AgensGraph vs. IBM Db2 Event Store vs. Ignite vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Graph DBMS
Relational DBMS

Event Store
Time Series DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

bitnine.net/agensgraph

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

ignite.apache.org

github.com/STSSoft/STSdb4

Technical documentation

bitnine.net/documentation

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

apacheignite.readme.io/docs

Developer

Bitnine Global Inc.

IBM

Apache Software Foundation

STS Soft SC

Initial release

2016

2017

2015

2011

Current release

2.1, December 2018

2.0

Apache Ignite 2.6

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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 and C++

C++, Java, .Net

Server operating systems

Linux
OS X
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Solaris
Windows

Windows

Data scheme

depending on used data model

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

through the embedded Spark runtime

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

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

.NET Client API

Supported programming languages

C
Java
JavaScript
Python

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#
Java

Server-side scripts

Stored procedures

yes

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard replication

yes (replicated cache)

none

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

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

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