DBMS > Apache IoTDB vs. InfinityDB vs. Sequoiadb vs. SiriDB vs. Yaacomo

System Properties Comparison Apache IoTDB vs. InfinityDB vs. Sequoiadb 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

A Java embedded Key-Value Store which extends the Java Map interface

NewSQL database with distributed OLTP and SQL

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

Document store
Relational DBMS

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	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

yaacomo.com

Technical documentation

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

boilerbay.com/infinitydb/manual

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.siridb.com

Developer

Apache Software Foundation

Boiler Bay Inc.

Sequoiadb Ltd.

Cesbit

Q2WEB GmbH

Initial release

2018

2002

2013

2017

2009

Current release

1.1.0, April 2023

4.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux

Android
Linux
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

proprietary protocol using JSON

HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

.Net
C++
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

none

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Document is locked during a transaction

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

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