DBMS > Badger vs. EXASOL vs. Fauna vs. SAP SQL Anywhere

System Properties Comparison Badger vs. EXASOL vs. Fauna vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

github.com/dgraph-io/badger

www.exasol.com

fauna.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

www.exasol.com/resources

docs.fauna.com

help.sap.com/docs/SAP_SQL_Anywhere

Developer

DGraph Labs

Exasol

Fauna, Inc.

SAP

formerly Sybase

Initial release

2017

2000

2014

1992

Current release

17, July 2015

License

Commercial or Open Source

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

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

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

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

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