DBMS > Apache IoTDB vs. Kinetica vs. RavenDB vs. SQL.JS vs. Transbase

System Properties Comparison Apache IoTDB vs. Kinetica vs. RavenDB vs. SQL.JS vs. Transbase

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

Fully vectorized database across both GPUs and CPUs

Open Source Operational and Transactional Enterprise NoSQL Document Database

Port of SQLite to JavaScript

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Graph DBMS
Spatial DBMS
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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.transaction.de/en/products/transbase.html

Technical documentation

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

docs.kinetica.com

ravendb.net/docs

sql.js.org/documentation/index.html

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Kinetica

Hibernating Rhinos

Alon Zakai

enhancements implemented by others

Transaction Software GmbH

Initial release

2018

2012

2010

2012

1987

Current release

1.1.0, April 2023

7.1, August 2021

5.4, July 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

AGPL version 3, commercial license available

Open Source

commercial

free development license

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++

JavaScript

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
macOS
Raspberry Pi
Windows

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language (RQL)

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JavaScript API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

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

Multi-source replication

none

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 or Eventual Consistency depending on configuration

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

yes

Access rights for users and roles on table level

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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