DBMS > Datomic vs. Google Cloud Datastore vs. Hive vs. MariaDB vs. Riak KV

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Hive vs. MariaDB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

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

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

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	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	91.04
Rank	#13	Overall
	#9	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.datomic.com

cloud.google.com/datastore

hive.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

docs.datomic.com

cloud.google.com/datastore/docs

cwiki.apache.org/confluence/display/Hive/Home

mariadb.com/kb/en/library

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

Developer

Cognitect

Google

Apache Software Foundation

initially developed by Facebook

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

The lead developer Monty Widenius is the original author of MySQL

OpenSource, formerly Basho Technologies

Initial release

2012

2008

2012

2009

Fork of MySQL, which was first released in 1995

2009

Current release

1.0.7075, December 2023

3.1.3, April 2022

11.3.2, February 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Apache version 2, commercial enterprise edition

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

C and C++

Erlang

Server operating systems

All OS with a Java VM

hosted

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
OS X

Data scheme

yes

schema-free

yes

Dynamic columns are supported

schema-free

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

restricted

SQL

Support of SQL

SQL-like query language (GQL)

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

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

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

Supported programming languages

Clojure
Java

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

C++
Java
PHP
Python

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

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

Server-side scripts

Stored procedures

yes

Transaction Functions

using Google App Engine

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Erlang

Triggers

By using transaction functions

Callbacks using the Google Apps Engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

several options for horizontal partitioning and Sharding

Sharding

no "single point of failure"

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

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

query execution via MapReduce

yes

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.

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

not for MyISAM storage engine

links between data sets can be stored

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

yes

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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