DBMS > Alibaba Cloud TSDB vs. Apache IoTDB vs. Ignite vs. IRONdb vs. Transbase

System Properties Comparison Alibaba Cloud TSDB vs. Apache IoTDB vs. Ignite vs. IRONdb vs. Transbase

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A stable, reliable, and cost-effective online high-performance time series database service

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.24
Rank	#306	Overall
	#26	Time Series DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

iotdb.apache.org

ignite.apache.org

www.circonus.com/solutions/time-series-database/

www.transaction.de/en/products/transbase.html

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

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

apacheignite.readme.io/docs

docs.circonus.com/irondb/category/getting-started

www.transaction.de/en/products/transbase/features.html

Developer

Alibaba

Apache Software Foundation

Circonus LLC.

Transaction Software GmbH

Initial release

2018

2015

2017

1987

Current release

1.1.0, April 2023

Apache Ignite 2.6

V0.10.20, January 2018

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java, .Net

C and C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

yes

text, numeric, histograms

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

HTTP REST

JDBC
Native API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

C
C#
C++
Go
Java
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

yes, in Lua

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes (replicated cache)

configurable replication factor, datacenter aware

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

Access managed on TSDB instance level

yes

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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