DBMS > AgensGraph vs. Couchbase vs. Kinetica vs. Microsoft Access vs. Netezza

System Properties Comparison AgensGraph vs. Couchbase vs. Kinetica vs. Microsoft Access vs. Netezza

Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Fully vectorized database across both GPUs and CPUs

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Graph DBMS
Relational DBMS

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS
Time Series 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	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

bitnine.net/agensgraph

www.couchbase.com

www.kinetica.com

www.microsoft.com/en-us/microsoft-365/access

www.ibm.com/products/netezza

Technical documentation

bitnine.net/documentation

docs.couchbase.com

docs.kinetica.com

developer.microsoft.com/en-us/access

Developer

Bitnine Global Inc.

Couchbase, Inc.

Kinetica

Microsoft

IBM

Initial release

2016

2011

2012

1992

2000

Current release

2.1, December 2018

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

7.1, August 2021

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Bundled with Microsoft Office

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++, Go and Erlang

C, C++

C++

Server operating systems

Linux
OS X
Windows

Linux

Windows

Not a real database server, but making use of DLLs

Linux

included in appliance

Data scheme

depending on used data model

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
OLE DB

Supported programming languages

C
Java
JavaScript
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

via the TAP protocol

yes

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

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Automatic Sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

none

Source-replica replication

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

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights for users and roles on table level

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

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