DBMS > Apache IoTDB vs. Axibase vs. Drizzle vs. GeoSpock

System Properties Comparison Apache IoTDB vs. Axibase vs. Drizzle vs. GeoSpock

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded 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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Spatial and temporal data processing engine for extreme data scale

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

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	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Website

iotdb.apache.org

axibase.com/docs/atsd/finance

geospock.com

Technical documentation

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

Developer

Apache Software Foundation

Axibase Corporation

Drizzle project, originally started by Brian Aker

GeoSpock

Initial release

2018

2013

2008

Current release

1.1.0, April 2023

15585

7.2.4, September 2012

2.0, September 2019

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

GNU GPL

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++

Java, Javascript

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

FreeBSD
Linux
OS X

hosted

Data scheme

yes

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

temporal, categorical

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

ANSI SQL for query only (using Presto)

APIs and other access methods

JDBC
Native API

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Java
PHP
Python
R
Ruby

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Automatic sharding

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

Multi-source replication
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

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

yes

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per table

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