DBMS > Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Infobright vs. MariaDB

System Properties Comparison Datomic vs. GeoSpock vs. Google Cloud Datastore vs. Infobright vs. MariaDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Spatial and temporal data processing engine for extreme data scale

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Website

www.datomic.com

geospock.com

cloud.google.com/datastore

ignitetech.com/softwarelibrary/infobrightdb

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

docs.datomic.com

cloud.google.com/datastore/docs

mariadb.com/kb/en/library

Developer

Cognitect

GeoSpock

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Initial release

2012

2008

2005

2009

Fork of MySQL, which was first released in 1995

Current release

1.0.6735, June 2023

2.0, September 2019

11.3.2, February 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2, commercial enterprise subscription available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

Java, Clojure

Java, Javascript

C and C++

Server operating systems

All OS with a Java VM

hosted

Linux
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Data scheme

yes

schema-free

yes

Dynamic columns are supported

Typing

predefined data types such as float or date

yes

yes, details here

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

Secondary indexes

yes

temporal, categorical

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language (GQL)

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

JDBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
Java

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

Transaction Functions

using Google App Engine

yes

PL/SQL compatibility added with version 10.3

Triggers

By using transaction functions

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Automatic sharding

Sharding

none

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication using Paxos

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

not for in-memory storage engine

In-memory capabilities

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

yes

recommended only for testing and development

yes

with MEMORY storage engine

User concepts

Access control

Access rights for users can be defined per table

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

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Market metrics

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Licensing and pricing models

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