DBMS > EventStoreDB vs. SAP HANA vs. TimescaleDB vs. Transbase

System Properties Comparison EventStoreDB vs. SAP HANA vs. TimescaleDB vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

In-memory, column based data store. Available as appliance or cloud service

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.eventstore.com

www.sap.com/products/hana.html

www.timescale.com

www.transaction.de/en/products/transbase.html

Technical documentation

developers.eventstore.com

help.sap.com/hana

docs.timescale.com

www.transaction.de/en/products/transbase/features.html

Developer

Event Store Limited

SAP

Timescale

Transaction Software GmbH

Initial release

2012

2010

2017

1987

Current release

21.2, February 2021

2.0 SPS07 (April 4, 2023), April 2023

2.13.0, November 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Server operating systems

Linux
Windows

Appliance or cloud-service

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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

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

full PostgreSQL SQL syntax

yes

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

SQLScript, R

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with hot standby and reads on replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

fine grained access rights according to SQL-standard

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