DBMS > AnzoGraph DB vs. Bangdb vs. OrigoDB vs. TerarkDB vs. VelocityDB

System Properties Comparison AnzoGraph DB vs. Bangdb vs. OrigoDB vs. TerarkDB vs. VelocityDB

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

Converged and high performance database for device data, events, time series, document and graph

A fully ACID in-memory object graph database

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Document store
Object oriented DBMS

Key-value store

Graph DBMS
Object oriented DBMS

Secondary database models

Spatial 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	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

cambridgesemantics.com/anzograph

bangdb.com

origodb.com

github.com/bytedance/terarkdb

velocitydb.com

Technical documentation

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

docs.bangdb.com

origodb.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

velocitydb.com/UserGuide

Developer

Cambridge Semantics

Sachin Sinha, BangDB

Robert Friberg et al

ByteDance, originally Terark

VelocityDB Inc

Initial release

2018

2012

2009

under the name LiveDB

2016

2011

Current release

2.3, January 2021

BangDB 2.0, October 2021

7.x

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD 3

Open Source

commercial

restricted open source version available

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++

C++

Server operating systems

Linux

Linux
Windows

Any that supports .NET

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

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

SQL like support with command line tool

APIs and other access methods

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

Proprietary protocol
RESTful HTTP API

.NET Client API
HTTP API
LINQ

C++ API
Java API

.Net

Supported programming languages

C++
Java
Python

C
C#
C++
Java
Python

.Net

C++
Java

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes, Notifications (with Streaming only)

yes

Domain Events

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

none

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

Write ahead log

yes

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Role based authorization

Based on Windows Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

Share this page