DBMS > Altibase vs. Badger vs. Firebolt vs. Microsoft Azure Cosmos DB

System Properties Comparison Altibase vs. Badger vs. Firebolt vs. Microsoft Azure Cosmos DB

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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.

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

altibase.com

github.com/dgraph-io/badger

www.firebolt.io

azure.microsoft.com/services/cosmos-db

Technical documentation

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

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

docs.firebolt.io

learn.microsoft.com/azure/cosmos-db

Developer

Altibase

DGraph Labs

Firebolt Analytics Inc.

Microsoft

Initial release

1999

2017

2020

2014

Current release

v7.3, 2023, August 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

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++

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI SQL-92

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

.Net
ODBC
RESTful HTTP API

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

Supported programming languages

C
C++
Java

Go
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

stored procedures and stored functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

depending on storage layer

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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