DBMS > Apache Druid vs. Apache IoTDB vs. Informix vs. OpenTenBase

System Properties Comparison Apache Druid vs. Apache IoTDB vs. Informix vs. OpenTenBase

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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

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

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	16.32
Rank	#35	Overall
	#21	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

druid.apache.org

iotdb.apache.org

www.ibm.com/products/informix

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

druid.apache.org/docs/latest/design

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

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Apache Software Foundation and contributors

Apache Software Foundation

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

OpenAtom Foundation, previously Tencent

Initial release

2012

2018

1984

Current release

30.0.0, June 2024

1.1.0, April 2023

14.10.FC5, November 2020

2.5, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

BSD-3

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++ and Java

Server operating systems

Linux
OS X
Unix

All OS with a Java VM (>= 1.8)

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
Native API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

yes

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)

Sharding

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

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users, groups and roles according to SQL-standard

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