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

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

Please select another system to include it in the comparison.

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

Open Source Time Series DBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Key-value store

Event Store
Time Series DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Website

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

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

siridb.com

www.timescale.com

Technical documentation

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

docs.siridb.com

docs.timescale.com

Developer

Atos Convergence Creators

IBM

Cesbit

Timescale

Initial release

2016

2017

Current release

1703

2.0

2.15.0, May 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

MIT License

Open Source

Apache 2.0

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

Java

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

Numeric data

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

LDAP

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

yes

Source-replica replication with hot standby and reads on replicas

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

Immediate 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 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

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Mudhakar Srivatsa
11 December 2023, IBM Research

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

How IBM Is Turning Db2 into an ‘AI Database’
3 June 2019, Datanami

provided by Google News

General availability: Latest version of the TimeScaleDB extension on Azure Database for PostgreSQL - Flexible Server
8 May 2024, azure.microsoft.com

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

Share this page