DBMS > Apache Druid vs. Apache IoTDB vs. Faircom DB vs. HBase vs. Manticore Search

System Properties Comparison Apache Druid vs. Apache IoTDB vs. Faircom DB vs. HBase vs. Manticore Search

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Key-value store
Relational DBMS

Wide column store

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

druid.apache.org

iotdb.apache.org

www.faircom.com/products/faircom-db

hbase.apache.org

manticoresearch.com

Technical documentation

druid.apache.org/docs/latest/design

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

hbase.apache.org/book.html

manual.manticoresearch.com

Developer

Apache Software Foundation and contributors

Apache Software Foundation

FairCom Corporation

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Manticore Software

Initial release

2012

2018

1979

2008

2017

Current release

29.0.1, April 2024

1.1.0, April 2023

V12, November 2020

2.3.4, January 2021

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Apache version 2

Open Source

GPL version 2

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

ANSI C, C++

Java

C++

Server operating systems

Linux
OS X
Unix

All OS with a Java VM (>= 1.8)

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
Unix
Windows

using Cygwin

FreeBSD
Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

yes

schema free, schema optional, schema required, partial schema,

schema-free, schema definition possible

Fixed schema

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

options to bring your own types, AVRO

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

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

SQL

Support of SQL

SQL for querying

SQL-like query language

yes, ANSI SQL with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
Native API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Java API
RESTful HTTP API
Thrift

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Coprocessors in Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Single row ACID (across millions of columns)

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

Yes, tunable from durable to delayed durability to in-memory

yes

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

In-memory capabilities

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

yes

User concepts

Access control

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

yes

Fine grained access rights according to SQL-standard with additional protections for files

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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