DBMS > Axibase vs. Fauna vs. HBase vs. Microsoft SQL Server

System Properties Comparison Axibase vs. Fauna vs. HBase vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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

Microsofts flagship relational DBMS

Primary database model

Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

axibase.com/docs/atsd/finance

fauna.com

hbase.apache.org

www.microsoft.com/en-us/sql-server

Technical documentation

docs.fauna.com

hbase.apache.org/book.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Axibase Corporation

Fauna, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Initial release

2013

2014

2008

1989

Current release

15585

2.3.4, January 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache version 2

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Java

C++

Server operating systems

Linux

hosted

Linux
Unix
Windows

using Cygwin

Linux
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

options to bring your own types, AVRO

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

yes

Coprocessors in Java

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

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

Immediate Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

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

fine grained access rights according to SQL-standard

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