DBMS > GridGain vs. Manticore Search vs. RocksDB vs. SingleStore

System Properties Comparison GridGain vs. Manticore Search vs. RocksDB vs. SingleStore

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

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

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Key-value store
Relational DBMS

Search engine

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

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

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Website

Technical documentation

www.gridgain.com/docs/index.html

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

docs.singlestore.com

Developer

GridGain Systems, Inc.

Manticore Software

Facebook, Inc.

SingleStore Inc.

Initial release

2007

2017

2013

Current release

GridGain 8.5.1

6.0, February 2023

9.2.1, May 2024

8.5, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

BSD

commercial

free developer edition available

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java, C++, .Net

C++

C++, Go

Server operating systems

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux

64 bit version required

Data scheme

yes

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.

yes

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

but no triggers and foreign keys

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

yes

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Synchronous replication based on Galera library

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Security Hooks for custom implementations

Fine grained access control via users, groups and roles

More information provided by the system vendor

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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