DBMS > AnzoGraph DB vs. Apache Doris vs. Google BigQuery vs. Riak KV vs. Solr

System Properties Comparison AnzoGraph DB vs. Apache Doris vs. Google BigQuery vs. Riak KV vs. Solr

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

Distributed, fault tolerant key-value store

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Search engine

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	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

cambridgesemantics.com/anzograph

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

cloud.google.com/bigquery

solr.apache.org

Technical documentation

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

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

www.tiot.jp/riak-docs/riak/kv/latest

solr.apache.org/resources.html

Developer

Cambridge Semantics

Apache Software Foundation, originally contributed from Baidu

Google

OpenSource, formerly Basho Technologies

Apache Software Foundation

Initial release

2018

2017

2010

2009

2006

Current release

2.3, January 2021

1.2.2, February 2023

3.2.0, December 2022

9.6.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2

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

Erlang

Java

Server operating systems

Linux

hosted

Linux
OS X

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic 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.

yes

Secondary indexes

yes

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

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

yes

Solr Parallel SQL Interface

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

HTTP API
Native Erlang Interface

Java API
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in JavaScript

Erlang

Java plugins

Triggers

yes

pre-commit hooks and post-commit hooks

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

none

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

links between data sets can be stored

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

optimistic locking

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)

yes, using Riak Security

yes

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