DBMS > Badger vs. H2 vs. Netezza vs. SAP SQL Anywhere

System Properties Comparison Badger vs. H2 vs. Netezza vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Data warehouse and analytics appliance part of IBM PureSystems

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

github.com/dgraph-io/badger

www.h2database.com

www.ibm.com/products/netezza

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

www.h2database.com/html/main.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

DGraph Labs

Thomas Mueller

IBM

SAP

formerly Sybase

Initial release

2017

2005

2000

1992

Current release

2.2.220, July 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

included in appliance

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

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