DBMS > Apache IoTDB vs. Axibase vs. Firebird vs. TempoIQ

System Properties Comparison Apache IoTDB vs. Axibase vs. Firebird vs. TempoIQ

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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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Firebird is an open source RDBMS forked from Borland's InterBase

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

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Website

iotdb.apache.org

axibase.com/docs/atsd/finance

www.firebirdsql.org

tempoiq.com (offline)

Technical documentation

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

www.firebirdsql.org/en/reference-manuals

Developer

Apache Software Foundation

Axibase Corporation

Firebird Foundation

TempoIQ

Initial release

2018

2013

2000

As fork of Borland's InterBase

2012

Current release

1.1.0, April 2023

15585

5.0.0, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Initial Developer's Public License

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

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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-like query language

yes

APIs and other access methods

JDBC
Native API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Java
PHP
Python
R
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

PSQL

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

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

Source-replica replication

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

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

Features a multi-generational MVCC architecture, readers do not block writers

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

Users with fine-grained authorization concept

simple authentication-based access control

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