DBMS > AnzoGraph DB vs. Bangdb vs. ObjectBox vs. OrigoDB vs. Rockset

System Properties Comparison AnzoGraph DB vs. Bangdb vs. ObjectBox vs. OrigoDB vs. Rockset

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

Extremely fast embedded database for small devices, IoT and Mobile

A fully ACID in-memory object graph database

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Object oriented DBMS

Document store
Object oriented DBMS

Document store

Secondary database models

Spatial DBMS

Time Series DBMS

Relational DBMS
Search engine

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

cambridgesemantics.com/anzograph

Technical documentation

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

Developer

Cambridge Semantics

Sachin Sinha, BangDB

ObjectBox Limited

Robert Friberg et al

Rockset

Initial release

2018

2012

2017

2009

under the name LiveDB

2019

Current release

2.3, January 2021

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD 3

Open Source

Apache License 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C and C++

C++

Server operating systems

Linux

Android
iOS
Linux
macOS
Windows

Linux
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

User defined using .NET types and collections

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

SQL

Support of SQL

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

SQL like support with command line tool

Read-only SQL queries, including JOINs

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

Proprietary native API

.NET Client API
HTTP API
LINQ

HTTP REST

Supported programming languages

C++
Java
Python

C
C#
C++
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes, Notifications (with Streaming only)

yes

Domain Events

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

none

horizontal partitioning

client side managed; servers are not synchronized

Automatic 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)

online/offline synchronization between client and server

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

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)

yes

Role based authorization

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

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More resources

Recent citations in the news

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

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

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

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

Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable?
19 September 2018, Forbes

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20 May 2024, Blocks & Files

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17 May 2024, Datanami

Data Management News for the Week of May 17; Updates from Anomalo, DataStax, Rockset & More
16 May 2024, Solutions Review

Rockset launches native support for hybrid vector and text search to power AI apps
16 May 2024, SiliconANGLE News

Rockset Hybrid Search Release Sets New Course for Vector Databases
17 May 2024, EnterpriseTalk

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