DBMS > Citus vs. Elasticsearch vs. RocksDB vs. TigerGraph vs. Valentina Server

System Properties Comparison Citus vs. Elasticsearch vs. RocksDB vs. TigerGraph vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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)

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Object-relational database and reports server

Primary database model

Secondary database models

Document store

Document store
Spatial DBMS
Vector DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.citusdata.com

www.elastic.co/elasticsearch

rocksdb.org

www.tigergraph.com

www.valentina-db.net

Technical documentation

docs.citusdata.com

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

github.com/facebook/rocksdb/wiki

docs.tigergraph.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Elastic

Facebook, Inc.

Paradigma Software

Initial release

2010

2013

2017

1999

Current release

8.1, December 2018

8.6, January 2023

8.11.4, April 2024

5.7.5

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Elastic 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

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

yes

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

SQL-like query language (GSQL)

yes

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

C++ API
Java API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

ODBC

Supported programming languages

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

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

C
C++
Go
Java
Perl
Python
Ruby

C++
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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.

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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