DBMS > Atos Standard Common Repository vs. IBM Db2 Event Store vs. TerminusDB

System Properties Comparison Atos Standard Common Repository vs. IBM Db2 Event Store vs. TerminusDB

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Distributed Event Store optimized for Internet of Things use cases

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Key-value store

Event Store
Time Series DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.15
Rank	#365	Overall
	#3	Event Stores
	#35	Time Series DBMS

Score	0.30
Rank	#325	Overall
	#27	Graph DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

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

terminusdb.com

Technical documentation

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

terminusdb.github.io/terminusdb/#

Developer

Atos Convergence Creators

IBM

DataChemist Ltd.

Initial release

2016

2017

2018

Current release

1703

2.0

11.0.0, January 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL V3

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

Java

C and C++

Prolog, Rust

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language (WOQL)

APIs and other access methods

LDAP

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages with LDAP bindings

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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 journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

Role-based access control

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