DBMS > Apache IoTDB vs. HBase vs. Interbase vs. Riak KV vs. TempoIQ

System Properties Comparison Apache IoTDB vs. HBase vs. Interbase vs. Riak KV vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

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

Light-weight proven RDBMS

originally from Borland

Distributed, fault tolerant key-value store

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

iotdb.apache.org

hbase.apache.org

www.embarcadero.com/products/interbase

tempoiq.com (offline)

Technical documentation

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

hbase.apache.org/book.html

docs.embarcadero.com/products/interbase

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Embarcadero

OpenSource, formerly Basho Technologies

TempoIQ

Initial release

2018

2008

1984

2009

2012

Current release

1.1.0, April 2023

2.3.4, January 2021

InterBase 2020, December 2019

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

Open Source

Apache version 2, commercial enterprise edition

commercial

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

Erlang

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Unix
Windows

using Cygwin

Android
iOS
Linux
OS X
Windows

Linux
OS X

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

export as XML data possible

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Interbase procedure and trigger language

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Sharding

no "single point of failure"

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

Multi-source replication
Source-replica replication

Interbase Change Views

selectable replication factor

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

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

yes

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

fine grained access rights according to SQL-standard

yes, using Riak Security

simple authentication-based access control

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