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

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

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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

An MPP-based analytics DBMS embracing the MySQL protocol

Large scale data warehouse service with append-only tables

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Graph DBMS
RDF store

Relational DBMS

Time Series DBMS

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.70
Rank	#136	Overall
	#11	Time Series DBMS

Website

cambridgesemantics.com/anzograph

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

cloud.google.com/bigquery

oss.oetiker.ch/rrdtool

Technical documentation

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

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

oss.oetiker.ch/rrdtool/doc

Developer

Cambridge Semantics

Apache Software Foundation, originally contributed from Baidu

Google

Tobias Oetiker

Initial release

2018

2017

2010

1999

Current release

2.3, January 2021

1.2.2, February 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux

hosted

HP-UX
Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

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

in-process shared library
Pipes

Supported programming languages

C++
Java
Python

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

Triggers

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

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

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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)

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