DBMS > AgensGraph vs. Apache Druid vs. RocksDB vs. SiteWhere vs. Solr

System Properties Comparison AgensGraph vs. Apache Druid vs. RocksDB vs. SiteWhere vs. Solr

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

M2M integration platform for persisting/querying time series data

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

bitnine.net/agensgraph

druid.apache.org

rocksdb.org

github.com/sitewhere/sitewhere

solr.apache.org

Technical documentation

bitnine.net/documentation

druid.apache.org/docs/latest/design

github.com/facebook/rocksdb/wiki

sitewhere1.sitewhere.io/index.html

solr.apache.org/resources.html

Developer

Bitnine Global Inc.

Apache Software Foundation and contributors

Facebook, Inc.

SiteWhere

Apache Software Foundation

Initial release

2016

2012

2013

2010

2006

Current release

2.1, December 2018

29.0.1, April 2024

9.2.1, May 2024

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache license v2

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

Linux

Linux
OS X
Windows

All OS with a Java VM

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

Data scheme

depending on used data model

yes

schema-less columns are supported

schema-free

predefined scheme

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

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL for querying

Solr Parallel SQL Interface

APIs and other access methods

Cypher Query Language
JDBC

JDBC
RESTful HTTP/JSON API

C++ API
Java API

HTTP REST

Java API
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, via HDFS, S3 or other storage engines

yes

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept

yes

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