DBMS > Apache IoTDB vs. KairosDB vs. Oracle Berkeley DB vs. SiriDB vs. Yaacomo

System Properties Comparison Apache IoTDB vs. KairosDB vs. Oracle Berkeley DB vs. SiriDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is 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

Distributed Time Series DBMS based on Cassandra or H2

Widely used in-process key-value store

Open Source Time Series DBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Relational DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

iotdb.apache.org

github.com/kairosdb/kairosdb

www.oracle.com/database/technologies/related/berkeleydb.html

siridb.com

yaacomo.com

Technical documentation

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

kairosdb.github.io

docs.oracle.com/cd/E17076_05/html/index.html

docs.siridb.com

Developer

Apache Software Foundation

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Cesbit

Q2WEB GmbH

Initial release

2018

2013

1994

2017

2009

Current release

1.1.0, April 2023

1.2.2, November 2018

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

MIT License

commercial

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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

JDBC
Native API

Graphite protocol
HTTP REST
Telnet API

HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java
JavaScript

Node.js
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

based on Cassandra

none

Sharding

horizontal partitioning

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

selectable replication factor

based on Cassandra

Source-replica replication

yes

Source-replica replication

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

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

simple password-based access control

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

Linux 6.5 With AMD P-State EPP Default Brings Performance & Power Efficiency Benefits For Ryzen Servers
21 September 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

AMD EPYC 8324P / 8324PN Siena 32-Core Siena Linux Server Performance Review
10 October 2023, Phoronix

provided by Google News

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, Datanami

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

Oracle buys Sleepycat Software
14 February 2006, MarketWatch

How to store financial market data for backtesting
26 January 2019, Towards Data Science

provided by Google News

Share this page