DBMS > AgensGraph vs. HEAVY.AI vs. Kinetica vs. Microsoft SQL Server vs. Oracle Coherence

System Properties Comparison AgensGraph vs. HEAVY.AI vs. Kinetica vs. Microsoft SQL Server vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

Oracles in-memory data grid solution

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

bitnine.net/agensgraph

github.com/heavyai/heavydb
www.heavy.ai

www.kinetica.com

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

www.oracle.com/java/coherence

Technical documentation

bitnine.net/documentation

docs.heavy.ai

docs.kinetica.com

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

Bitnine Global Inc.

HEAVY.AI, Inc.

Kinetica

Microsoft

Oracle

Initial release

2016

2012

1989

2007

Current release

2.1, December 2018

5.10, January 2022

7.1, August 2021

SQL Server 2022, November 2022

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C, C++

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

All OS with a Java VM

Data scheme

depending on used data model

yes

schema-free

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

SQL-like DML and DDL statements

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

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

JCache
JPA
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

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

.Net
C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

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

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Round robin

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Source-replica replication

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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