DBMS > Apache Druid vs. Manticore Search vs. Stardog vs. TerminusDB vs. Tibero

System Properties Comparison Apache Druid vs. Manticore Search vs. Stardog vs. TerminusDB vs. Tibero

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

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
RDF store

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

Score	2.70
Rank	#98	Overall
	#50	Relational DBMS
	#7	Time Series DBMS

Score	0.23
Rank	#300	Overall
	#21	Search engines

Score	1.78
Rank	#130	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.15
Rank	#326	Overall
	#30	Graph DBMS

Score	1.40
Rank	#153	Overall
	#70	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

druid.apache.org/docs/latest/design

manual.manticoresearch.com

docs.stardog.com

terminusdb.github.io/terminusdb/#

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation and contributors

Manticore Software

Stardog-Union

DataChemist Ltd.

TmaxSoft

Initial release

2012

2017

2010

2018

2003

Current release

30.0.0, June 2024

6.0, February 2023

7.3.0, May 2020

11.0.0, January 2023

7, September 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPL version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3

commercial

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

Prolog, Rust

C and Assembler

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
macOS
Windows

Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-less columns are supported

Fixed schema

schema-free and OWL/RDFS-schema support

yes

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

Import/export of XML data possible

yes

Secondary indexes

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

yes

Persistent Stored Procedure (PSM)

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

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

none

Graph Partitioning

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Synchronous replication based on Galera library

Multi-source replication in HA-Cluster

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

in-memory journaling

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

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

Access rights for users and roles

Role-based access control

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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