DBMS > IBM Db2 Event Store vs. PostGIS vs. Snowflake vs. Transbase

System Properties Comparison IBM Db2 Event Store vs. PostGIS vs. Snowflake vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Spatial extension of PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

Event Store
Time Series DBMS

Spatial DBMS

Relational 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	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

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

postgis.net

www.snowflake.com

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

Technical documentation

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

postgis.net/documentation

docs.snowflake.net/manuals/index.html

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

Developer

IBM

Snowflake Computing Inc.

Transaction Software GmbH

Initial release

2017

2005

2014

1987

Current release

2.0

3.4.2, February 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL v2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

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

Linux, macOS, Windows for the developer addition

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

based on PostgreSQL

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

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

yes

based on PostgreSQL

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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