DBMS > AnzoGraph DB vs. Axibase vs. Lovefield vs. VoltDB

System Properties Comparison AnzoGraph DB vs. Axibase vs. Lovefield vs. VoltDB

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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

Embeddable relational database for web apps written in pure JavaScript

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

cambridgesemantics.com/anzograph

axibase.com/docs/atsd/finance

google.github.io/lovefield

www.voltdb.com

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.voltdb.com

Developer

Cambridge Semantics

Axibase Corporation

Google

VoltDB Inc.

Initial release

2018

2013

2014

2010

Current release

2.3, January 2021

15585

2.1.12, February 2017

11.3, April 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

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

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

JavaScript

Java, C++

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

for development

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

via JavaScript builder pattern

yes

only a subset of SQL 99

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

Go
Java
PHP
Python
R
Ruby

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

none

Multi-source 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

Foreign keys

Referential integrity

not needed in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Snapshots and command logging

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users and roles

Users and roles with access to stored procedures

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More resources

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