DBMS > Apache Druid vs. Fujitsu Enterprise Postgres vs. H2 vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison Apache Druid vs. Fujitsu Enterprise Postgres vs. H2 vs. RocksDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

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

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

druid.apache.org

www.postgresql.fastware.com

www.h2database.com

rocksdb.org

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

Technical documentation

druid.apache.org/docs/latest/design

www.postgresql.fastware.com/product-manuals

www.h2database.com/html/main.html

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation and contributors

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Thomas Mueller

Facebook, Inc.

SAP

formerly Sybase

Initial release

2012

2005

2013

1992

Current release

29.0.1, April 2024

Fujitsu Enterprise Postgres 14, January 2022

2.2.220, July 2023

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

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

Open Source

BSD

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

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

All OS with a Java VM

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

partitioning by range, list and by hash

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

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

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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Licensing and pricing models

Core based licensing
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