DBMS > AnzoGraph DB vs. Google BigQuery vs. OceanBase vs. TinkerGraph

System Properties Comparison AnzoGraph DB vs. Google BigQuery vs. OceanBase vs. TinkerGraph

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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

Large scale data warehouse service with append-only tables

A distributed, high available RDBMS compatible with Oracle and MySQL

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Graph DBMS
RDF store

Relational DBMS

Graph DBMS

Secondary database models

Document store
Wide column store

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Trend Chart

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

cambridgesemantics.com/anzograph

cloud.google.com/bigquery

en.oceanbase.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

cloud.google.com/bigquery/docs

en.oceanbase.com/docs/oceanbase-database

Developer

Cambridge Semantics

Google

OceanBase

previously Alibaba and Ant Group

Initial release

2018

2010

2009

Current release

2.3, January 2021

4.3.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

Linux

hosted

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

TinkerPop 3

Supported programming languages

C++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Groovy
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication using Paxos

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

Immediate Consistency

none

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles according to SQL-standard

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