DBMS > Apache IoTDB vs. atoti vs. Brytlyt vs. Derby

System Properties Comparison Apache IoTDB vs. atoti vs. Brytlyt vs. Derby

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Editorial information provided by DB-Engines

Name

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Time Series DBMS

Object oriented DBMS

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Website

Technical documentation

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

docs.atoti.io

docs.brytlyt.io

db.apache.org/derby/manuals/index.html

Developer

Apache Software Foundation

ActiveViam

Brytlyt

Apache Software Foundation

Initial release

2018

2016

1997

Current release

1.1.0, April 2023

5.0, August 2023

10.17.1.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free versions available

commercial

Open Source

Apache version 2

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, C++ and CUDA

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

All OS with a Java VM

Data scheme

yes

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Multidimensional Expressions (MDX)

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java

Server-side scripts

Stored procedures

yes

Python

user defined functions

in PL/pgSQL

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding, horizontal partitioning

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

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

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