DBMS > H2 vs. HBase vs. NuoDB vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison H2 vs. HBase vs. NuoDB vs. RocksDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.h2database.com

hbase.apache.org

www.3ds.com/nuodb-distributed-sql-database

rocksdb.org

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

Technical documentation

www.h2database.com/html/main.html

hbase.apache.org/book.html

doc.nuodb.com

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Thomas Mueller

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Dassault Systèmes

originally NuoDB, Inc.

Facebook, Inc.

SAP

formerly Sybase

Initial release

2005

2008

2013

1992

Current release

2.2.220, July 2023

2.3.4, January 2021

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

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

Open Source

Apache version 2

commercial

limited edition free

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

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

Coprocessors in Java

Java, SQL

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

data is dynamically stored/cached on the nodes where it is read/written

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

yes

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

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

tunable commit protocol

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

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

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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