DBMS > H2 vs. Manticore Search vs. MySQL vs. Rockset vs. Stardog

System Properties Comparison H2 vs. Manticore Search vs. MySQL vs. Rockset vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Widely used open source RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Document store

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

www.h2database.com/html/main.html

manual.manticoresearch.com

dev.mysql.com/doc

docs.rockset.com

docs.stardog.com

Developer

Thomas Mueller

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Rockset

Stardog-Union

Initial release

2005

2017

1995

2019

2010

Current release

2.2.220, July 2023

6.0, February 2023

8.4.0, April 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

C and C++

C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

Fixed schema

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

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

yes

dynamic typing

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

yes

ingestion from XML files supported

Import/export of XML data possible

Secondary indexes

yes

full-text index on all search fields

yes

all fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

Read-only SQL queries, including JOINs

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

Access rights for users and roles

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