DBMS > AnzoGraph DB vs. Google BigQuery vs. OrientDB vs. Sequoiadb

System Properties Comparison AnzoGraph DB vs. Google BigQuery vs. OrientDB vs. Sequoiadb

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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

Multi-model DBMS (Document, Graph, Key/Value)

NewSQL database with distributed OLTP and SQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store
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	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

cambridgesemantics.com/anzograph

cloud.google.com/bigquery

orientdb.org

www.sequoiadb.com

Technical documentation

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

cloud.google.com/bigquery/docs

www.orientdb.com/docs/last/index.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Cambridge Semantics

Google

OrientDB LTD; CallidusCloud; SAP

Sequoiadb Ltd.

Initial release

2018

2010

2013

Current release

2.3, January 2021

3.2.29, March 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Apache version 2

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

Server operating systems

Linux

hosted

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

yes

SQL-like query language, no joins

SQL-like query language

APIs and other access methods

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

RESTful HTTP/JSON API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

proprietary protocol using JSON

Supported programming languages

C++
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

Java, Javascript

JavaScript

Triggers

Hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

relationship in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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 and roles; record level security configurable

simple password-based access control

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