DBMS > DataFS vs. RocksDB vs. Solr vs. TinkerGraph vs. Typesense

System Properties Comparison DataFS vs. RocksDB vs. Solr vs. TinkerGraph vs. Typesense

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Secondary database models

Graph DBMS

Spatial DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

newdatabase.com

rocksdb.org

solr.apache.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

typesense.org

Technical documentation

dev.mobiland.com/Overview.xsp

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

typesense.org/docs

Developer

Mobiland AG

Facebook, Inc.

Apache Software Foundation

Initial release

2018

2013

2006

2009

2015

Current release

1.1.263, October 2022

9.2.1, May 2024

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

GPL V3

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

C++

Java

C++

Server operating systems

Windows

Linux

All OS with a Java VM

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

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

yes

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

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Solr Parallel SQL Interface

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

C++ API
Java API

Java API
RESTful HTTP/JSON API

TinkerPop 3

RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

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

Groovy
Java

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

Java plugins

Triggers

no, except callback-events from server when changes happened

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication using RAFT

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

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

optional

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

Windows-Profile

yes

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