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

System Properties Comparison Apache Druid vs. Couchbase vs. Manticore Search 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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

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

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

druid.apache.org/docs/latest/design

docs.couchbase.com

manual.manticoresearch.com

terminusdb.github.io/terminusdb/#

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

Developer

Apache Software Foundation and contributors

Couchbase, Inc.

Manticore Software

DataChemist Ltd.

TmaxSoft

Initial release

2012

2011

2017

2018

2003

Current release

29.0.1, April 2024

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

6.0, February 2023

11.0.0, January 2023

6, April 2015

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GPL version 2

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, C++, Go and Erlang

C++

Prolog, Rust

C and Assembler

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-less columns are supported

schema-free

Fixed schema

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL for querying

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

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

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

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

JavaScript
Python

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

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

yes

Persistent Stored Procedure (PSM)

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Automatic Sharding

Sharding

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

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

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication based on Galera library

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

Ephemeral buckets

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Role-based access control

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

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