DBMS > Elasticsearch vs. RocksDB vs. SAP HANA vs. Sphinx vs. TimesTen

System Properties Comparison Elasticsearch vs. RocksDB vs. SAP HANA vs. Sphinx vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

In-memory, column based data store. Available as appliance or cloud service

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

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

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.elastic.co/elasticsearch

rocksdb.org

www.sap.com/products/hana.html

sphinxsearch.com

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

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/facebook/rocksdb/wiki

help.sap.com/hana

sphinxsearch.com/docs

docs.oracle.com/database/timesten-18.1

Developer

Elastic

Facebook, Inc.

SAP

Sphinx Technologies Inc.

Oracle, TimesTen Performance Software, HP

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

Initial release

2010

2013

2010

2001

1998

Current release

8.6, January 2023

9.2.1, May 2024

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Elastic License

Open Source

BSD

commercial

Open Source

GPL version 2, commercial licence available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

All OS with a Java VM

Linux

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

C++ API
Java API

JDBC
ODBC

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

SQLScript, R

PL/SQL

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

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

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

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.

Memcached and Redis integration

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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