DBMS > Elasticsearch vs. Manticore Search vs. Riak TS vs. RocksDB vs. TigerGraph

System Properties Comparison Elasticsearch vs. Manticore Search vs. Riak TS vs. RocksDB vs. TigerGraph

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

Multi-storage database for search, including full-text search.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.elastic.co/elasticsearch

manticoresearch.com

rocksdb.org

www.tigergraph.com

Technical documentation

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

manual.manticoresearch.com

www.tiot.jp/riak-docs/riak/ts/latest

github.com/facebook/rocksdb/wiki

docs.tigergraph.com

Developer

Elastic

Manticore Software

Open Source, formerly Basho Technologies

Facebook, Inc.

Initial release

2010

2017

2015

2013

2017

Current release

8.6, January 2023

6.0, February 2023

3.0.0, September 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

GPL version 2

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Erlang

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Linux
OS X

Linux

Data scheme

schema-free

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

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

SQL-like query language (GSQL)

APIs and other access methods

Java API
RESTful HTTP/JSON API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP API
Native Erlang Interface

C++ API
Java API

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

Supported programming languages

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Go
Java
Perl
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

Erlang

yes

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

selectable replication factor

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

Eventual Consistency

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

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Relationships in graphs

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

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 Manticore index.

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

Role-based access control

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