DBMS > AgensGraph vs. CrateDB vs. VoltDB

System Properties Comparison AgensGraph vs. CrateDB vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

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

Distributed Database based on Lucene

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
Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

bitnine.net/agensgraph

cratedb.com

www.voltdb.com

Technical documentation

bitnine.net/documentation

cratedb.com/docs

docs.voltdb.com

Developer

Bitnine Global Inc.

Crate

VoltDB Inc.

Initial release

2016

2013

2010

Current release

2.1, December 2018

5.8.1, August 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 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

Java, C++

Server operating systems

Linux
OS X
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X

for development

Data scheme

depending on used data model

Flexible Schema (defined schema, partial schema, 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

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

only a subset of SQL 99

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions (Javascript)

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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

Snapshots and command logging

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Graph DBMS Performance Comparison AgensGraph vs. Neo4j
29 June 2017, businesswire.com

Bitnine Releases AgensGraph 2.1, the Multi-model Graph Database Optimized for the Legacy Environment
29 January 2019, businesswire.com

AGEDB Technology Ltd. (CVE: AGET) Announces Strategic Joint R&D Collaboration with Ovation Solutions Inc. and Bitnine Co. Ltd. (357880.KQ) to Enhance Microsoft Azure Stack Hub
27 August 2024, Yahoo Finance

Bitnine Global and CGI Enter $3 Million System Integrator License Agreement
6 September 2024, The Malaysian Reserve

Bitnine: The Newly Revealed ‘AI Teacher’ Powered by Graph Database Delivers Hyper-Personalized Learning Experience
25 March 2019, businesswire.com

provided by Google News

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9 July 2024, PR Newswire

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

Crate.io raises $10M to grow its database platform
15 June 2021, VentureBeat

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

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31 August 2021, PR Newswire

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16 October 2023, YourStory

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

VoltDB Announces Key New Hires
26 October 2021, citybiz

provided by Google News

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