DBMS > Altibase vs. Badger vs. Datomic vs. Snowflake

System Properties Comparison Altibase vs. Badger vs. Datomic vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

altibase.com

github.com/dgraph-io/badger

www.datomic.com

www.snowflake.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

godoc.org/github.com/dgraph-io/badger

docs.datomic.com

docs.snowflake.net/manuals/index.html

Developer

Altibase

DGraph Labs

Cognitect

Snowflake Computing Inc.

Initial release

1999

2017

2012

2014

Current release

v7.3, 2023, August 2023

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

commercial

limited edition free

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

C++

Java, Clojure

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

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

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

ANSI SQL-92

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
C++
Java

Clojure
Java

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Transaction Functions

user defined functions

Triggers

yes

By using transaction functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

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