DBMS > Datomic vs. HBase vs. Riak KV vs. SiriDB vs. Snowflake

System Properties Comparison Datomic vs. HBase vs. Riak KV vs. SiriDB vs. Snowflake

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Distributed, fault tolerant key-value store

Open Source Time Series DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Wide column store

Key-value store

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

Time Series DBMS

Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

docs.datomic.com

hbase.apache.org/book.html

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

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

Cognitect

Apache Software Foundation

Apache top-level project, originally developed by Powerset

OpenSource, formerly Basho Technologies

Cesbit

Snowflake Computing Inc.

Initial release

2012

2008

2009

2017

2014

Current release

1.0.6735, June 2023

2.3.4, January 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

MIT License

commercial

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.

Implementation language

Java, Clojure

Java

Erlang

Server operating systems

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

Linux
OS X

Linux

hosted

Data scheme

yes

schema-free, schema definition possible

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

Numeric data

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

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

HTTP API
Native Erlang Interface

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Coprocessors in Java

Erlang

user defined functions

Triggers

By using transaction functions

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

no "single point of failure"

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

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

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

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes, using Riak Security

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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