DBMS > EventStoreDB vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Riak TS vs. Transbase

System Properties Comparison EventStoreDB vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Riak TS vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.eventstore.com

azure.microsoft.com/services/synapse-analytics

www.microsoft.com/en-us/sql-server

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

Technical documentation

developers.eventstore.com

docs.microsoft.com/azure/synapse-analytics

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/ts/latest

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

Developer

Event Store Limited

Microsoft

Open Source, formerly Basho Technologies

Transaction Software GmbH

Initial release

2012

2016

1989

2015

1987

Current release

21.2, February 2021

SQL Server 2022, November 2022

3.0.0, September 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Erlang

C and C++

Server operating systems

Linux
Windows

hosted

Linux
Windows

Linux
OS X

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

yes, limited

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
Java
PHP

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

links between datasets can be stored

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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