DBMS > Datomic vs. FatDB vs. Microsoft Azure Cosmos DB vs. SingleStore vs. Solr

System Properties Comparison Datomic vs. FatDB vs. Microsoft Azure Cosmos DB vs. SingleStore vs. Solr

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Globally distributed, horizontally scalable, multi-model database service

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.datomic.com

azure.microsoft.com/services/cosmos-db

www.singlestore.com

solr.apache.org

Technical documentation

docs.datomic.com

learn.microsoft.com/azure/cosmos-db

docs.singlestore.com

solr.apache.org/resources.html

Developer

Cognitect

FatCloud

Microsoft

SingleStore Inc.

Apache Software Foundation

Initial release

2012

2014

2013

2006

Current release

1.0.7075, December 2023

8.5, January 2024

9.6.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

free developer edition available

Open Source

Apache Version 2

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java, Clojure

C++, Go

Java

Server operating systems

All OS with a Java VM

Windows

hosted

Linux

64 bit version required

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

JSON types

yes

supports customizable data types and automatic typing

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

All properties auto-indexed by default

yes

All search fields are automatically indexed

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

yes

but no triggers and foreign keys

Solr Parallel SQL Interface

APIs and other access methods

RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via applications

JavaScript

yes

Java plugins

Triggers

By using transaction functions

yes

via applications

JavaScript

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor

yes

Implicit feature of the cloud service

Source-replica replication

stores two copies of each physical data partition on two separate nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

can define user-defined aggregate functions for map-reduce-style calculations

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Can implement custom security layer via applications

Access rights can be defined down to the item level

Fine grained access control via users, groups and roles

yes

More information provided by the system vendor

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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