DBMS > Apache Druid vs. JanusGraph vs. Manticore Search vs. OpenSearch

System Properties Comparison Apache Druid vs. JanusGraph vs. Manticore Search vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Multi-storage database for search, including full-text search.

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

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Vector DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	16.36
Rank	#37	Overall
	#4	Search engines

Website

druid.apache.org

janusgraph.org

manticoresearch.com

github.com/opensearch-project
opensearch.org

Technical documentation

druid.apache.org/docs/latest/design

docs.janusgraph.org

manual.manticoresearch.com

opensearch.org/docs/latest

Developer

Apache Software Foundation and contributors

Linux Foundation; originally developed as Titan by Aurelius

Manticore Software

Amazon Web Services

Initial release

2012

2017

2021

Current release

29.0.1, April 2024

0.6.3, February 2023

6.0, February 2023

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Apache 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

C++

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Unix
Windows

FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Data scheme

yes

schema-less columns are supported

yes

Fixed schema

schema-free

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

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL for querying

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Java API
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Clojure
Java
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

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

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

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

User concepts

Access control

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

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,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Licensing and pricing models

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