DBMS > GridGain vs. H2GIS vs. MySQL vs. QuestDB vs. UniData,UniVerse

System Properties Comparison GridGain vs. H2GIS vs. MySQL vs. QuestDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of H2

Widely used open source RDBMS

A high performance open source SQL database for time series data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store
Relational DBMS

Spatial DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Multivalue DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Relational 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	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

www.gridgain.com/docs/index.html

www.h2gis.org/docs/home

dev.mysql.com/doc

questdb.io/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

GridGain Systems, Inc.

CNRS

Oracle

since 2010, originally MySQL AB, then Sun

QuestDB Technology Inc

Rocket Software

Initial release

2007

2013

1995

2014

1985

Current release

GridGain 8.5.1

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

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++, .Net

Java

C and C++

Java (Zero-GC), C++, Rust

Server operating systems

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

SQL with time-series extensions

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

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

yes

based on H2

yes

proprietary syntax

yes

Triggers

yes (cache interceptors and events)

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

based on H2

Multi-source replication
Source-replica replication

Source-replica replication with eventual consistency

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID for single-table writes

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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.

yes

through memory mapped files

User concepts

Access control

Security Hooks for custom implementations

yes

based on H2

Users with fine-grained authorization concept

no user groups or roles

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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