DBMS > HugeGraph vs. OpenSearch vs. SQL.JS vs. SQLite vs. Titan

System Properties Comparison HugeGraph vs. OpenSearch vs. SQL.JS vs. SQLite vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

A fast-speed and highly-scalable Graph DBMS

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Port of SQLite to JavaScript

Widely used embeddable, in-process RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Vector DBMS

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

github.com/opensearch-project
opensearch.org

sql.js.org

www.sqlite.org

github.com/thinkaurelius/titan

Technical documentation

hugegraph.apache.org/docs

opensearch.org/docs/latest

sql.js.org/documentation/index.html

www.sqlite.org/docs.html

github.com/thinkaurelius/titan/wiki

Developer

Baidu

Amazon Web Services

Alon Zakai

enhancements implemented by others

Dwayne Richard Hipp

Aurelius, owned by DataStax

Initial release

2018

2021

2012

2000

2012

Current release

0.9

2.5.0, January 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Public Domain

Open Source

Apache license, version 2.0

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.

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

Java

JavaScript

Java

Server operating systems

Linux
macOS
Unix

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

also supports composite index and range index

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
RESTful HTTP/JSON API

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Groovy
Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users, roles and permissions

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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