DBMS > RocksDB vs. Sphinx vs. TimesTen vs. Ultipa

System Properties Comparison RocksDB vs. Sphinx vs. TimesTen vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

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

Open source search engine for searching in data from different sources, e.g. relational databases

In-Memory RDBMS compatible to Oracle

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

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

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

rocksdb.org

sphinxsearch.com

www.oracle.com/database/technologies/related/timesten.html

www.ultipa.com

Technical documentation

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

docs.oracle.com/database/timesten-18.1

www.ultipa.com/document

Developer

Facebook, Inc.

Sphinx Technologies Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Ultipa

Initial release

2013

2001

1998

2019

Current release

8.11.4, April 2024

3.5.1, February 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD

Open Source

GPL version 2, commercial licence 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

C++

Server operating systems

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language (SphinxQL)

yes

APIs and other access methods

C++ API
Java API

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C++
Java
PL/SQL

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

by means of logfiles and checkpoints

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

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