DBMS > AnzoGraph DB vs. Axibase vs. Couchbase vs. HBase vs. Netezza

System Properties Comparison AnzoGraph DB vs. Axibase vs. Couchbase vs. HBase vs. Netezza

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

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

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

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

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

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

cambridgesemantics.com/anzograph

axibase.com/docs/atsd/finance

www.couchbase.com

hbase.apache.org

www.ibm.com/products/netezza

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.couchbase.com

hbase.apache.org/book.html

Developer

Cambridge Semantics

Axibase Corporation

Couchbase, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM

Initial release

2018

2013

2011

2008

2000

Current release

2.3, January 2021

15585

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

2.3.4, January 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

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

Open Source

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

Open Source

Apache version 2

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

Java

C, C++, Go and Erlang

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

Linux

included in appliance

Data scheme

Schema-free and OWL/RDFS-schema support

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

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

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

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
Python

Go
Java
PHP
Python
R
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

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

yes

Coprocessors in Java

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Automatic Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

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

Ephemeral buckets

yes

User concepts

Access control

Access rights for users and roles

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

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

Users with fine-grained authorization concept

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