DBMS > Dgraph vs. FatDB vs. Kinetica vs. SAP SQL Anywhere

System Properties Comparison Dgraph vs. FatDB vs. Kinetica vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Distributed and scalable native Graph DBMS

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Graph DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

dgraph.io

www.kinetica.com

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

Technical documentation

dgraph.io/docs

docs.kinetica.com

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Dgraph Labs, Inc.

FatCloud

Kinetica

SAP

formerly Sybase

Initial release

2016

2012

1992

Current release

7.1, August 2021

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Server operating systems

Linux
OS X
Windows

Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

Via inetgration in SQL Server

SQL-like DML and DDL statements

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

via applications

user defined functions

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

Triggers

yes

via applications

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

User concepts

Access control

Planned for future releases

Can implement custom security layer via applications

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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