DBMS > AnzoGraph DB vs. Geode vs. Interbase vs. Kinetica vs. RocksDB

System Properties Comparison AnzoGraph DB vs. Geode vs. Interbase vs. Kinetica vs. RocksDB

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Light-weight proven RDBMS

originally from Borland

Fully vectorized database across both GPUs and CPUs

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Spatial DBMS
Time Series 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	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

cambridgesemantics.com/anzograph

geode.apache.org

www.embarcadero.com/products/interbase

www.kinetica.com

rocksdb.org

Technical documentation

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

geode.apache.org/docs

docs.embarcadero.com/products/interbase

docs.kinetica.com

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Embarcadero

Kinetica

Facebook, Inc.

Initial release

2018

2002

1984

2012

2013

Current release

2.3, January 2021

1.1, February 2017

InterBase 2020, December 2019

7.1, August 2021

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

C++

Server operating systems

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Android
iOS
Linux
OS X
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language (OQL)

yes

SQL-like DML and DDL statements

APIs and other access methods

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

Java Client API
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C++
Java
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

yes

Interbase procedure and trigger language

user defined functions

Triggers

yes

Cache Event Listeners

yes

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

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

Interbase Change Views

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Access rights for users and roles

Access rights per client and object definable

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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