DBMS > Fujitsu Enterprise Postgres vs. OrientDB vs. RocksDB vs. Splunk vs. Teradata

System Properties Comparison Fujitsu Enterprise Postgres vs. OrientDB vs. RocksDB vs. Splunk vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

Multi-model DBMS (Document, Graph, Key/Value)

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

Analytics Platform for Big Data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.postgresql.fastware.com

Technical documentation

www.postgresql.fastware.com/product-manuals

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

docs.teradata.com

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Splunk Inc.

Teradata

Initial release

2010

2013

2003

1984

Current release

Fujitsu Enterprise Postgres 14, January 2022

3.2.29, March 2024

9.2.1, May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSD

commercial

Limited free edition and free developer edition available

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
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL-like query language, no joins

Splunk Search Processing Language for search commands

yes

SQL 2016 + extensions

APIs and other access methods

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

HTTP REST

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

Java, Javascript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

horizontal partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

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

Access rights for users and roles; record level security configurable

Access rights for users and roles

fine grained access rights according to SQL-standard

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