DBMS > Datomic vs. IBM Db2 vs. Informix vs. Memcached vs. Snowflake

System Properties Comparison Datomic vs. IBM Db2 vs. Informix vs. Memcached 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

Common in IBM host environments, 2 different versions for host and Windows/Linux

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

In-memory key-value store, originally intended for caching

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

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Key-value store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.datomic.com

www.ibm.com/products/db2

www.ibm.com/products/informix

www.memcached.org

www.snowflake.com

Technical documentation

docs.datomic.com

www.ibm.com/docs/en/db2

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

Developer

Cognitect

IBM

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

Initial release

2012

1983

host version

1984

2003

2014

Current release

1.0.6735, June 2023

12.1, October 2016

14.10.FC5, November 2020

1.6.27, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

free version is available

commercial

free developer edition available

Open Source

BSD 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

C and C++

C, C++ and Java

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

user defined functions

Triggers

By using transaction functions

yes

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

only with Windows/Unix/Linux Version

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

Users with fine-grained authentication, authorization, and auditing controls

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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