DBMS > AnzoGraph DB vs. Apache Doris vs. Google BigQuery vs. Linter

System Properties Comparison AnzoGraph DB vs. Apache Doris vs. Google BigQuery vs. Linter

Please select another system to include it in the comparison.

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

An MPP-based analytics DBMS embracing the MySQL protocol

Large scale data warehouse service with append-only tables

RDBMS for high security requirements

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

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	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Website

cambridgesemantics.com/anzograph

doris.apache.org
github.com/apache/doris

cloud.google.com/bigquery

linter.ru

Technical documentation

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

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

Developer

Cambridge Semantics

Apache Software Foundation, originally contributed from Baidu

Google

relex.ru

Initial release

2018

2017

2010

1990

Current release

2.3, January 2021

1.2.2, February 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

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 and C++

Server operating systems

Linux

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

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

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

JDBC
MySQL client

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Python

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Source-replica replication

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

Foreign keys

Referential integrity

not needed in graphs

yes

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

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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.