DBMS > Altibase vs. Badger vs. FatDB vs. Microsoft Azure Synapse Analytics vs. OushuDB

System Properties Comparison Altibase vs. Badger vs. FatDB vs. Microsoft Azure Synapse Analytics vs. OushuDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

An enterprise grade, high-performance RDBMS

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

Key-value store

Document store
Key-value store

Relational DBMS

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

altibase.com

github.com/dgraph-io/badger

azure.microsoft.com/services/synapse-analytics

www.oushu.com/product/oushuDB

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

godoc.org/github.com/dgraph-io/badger

docs.microsoft.com/azure/synapse-analytics

www.oushu.com/documentation

Developer

Altibase

DGraph Labs

FatCloud

Microsoft

Oushu

Initial release

1999

2017

2012

2016

Current release

v7.3, 2023, August 2023

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

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++

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Solaris
Windows

Windows

hosted

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

Via inetgration in SQL Server

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

C
C++
Java

C#
Java
PHP

C
C++

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

via applications

Transact SQL

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

yes

Kerberos, SSL and role based access

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