DBMS > Apache IoTDB vs. EsgynDB vs. Sadas Engine vs. Teradata

System Properties Comparison Apache IoTDB vs. EsgynDB vs. Sadas Engine vs. Teradata

Please select another system to include it in the comparison.

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.teradata.com

Developer

Apache Software Foundation

Esgyn

SADAS s.r.l.

Teradata

Initial release

2018

2015

2006

1984

Current release

1.1.0, April 2023

8.0

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version available

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++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

AIX
Linux
Windows

hosted
Linux

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

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Sharding

Hashing

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

Multi-source replication between multi datacenters

none

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

managed by 'Learn by Usage'

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

show all

Recent citations in the news

AMD Zen 5 Not Affected By Inception/SRSO, mitigations=off Yields No Benefit On Ryzen 9000 Series
6 September 2024, Phoronix

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

AMD EPYC 8534P / EPYC 8534PN Benchmarks - Siena Delivers Incredible Value & Energy Efficiency For Linux Servers Review
29 November 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

provided by Google News

Teradata wants you to think differently about data and innovation – and take inspiration from the likes of Shazam
17 September 2024, ITPro

Teradata: Award-Winning Tech Firm Has Capital Gains Potential At Undervalued Price (NYSE:TDC)
20 September 2024, Seeking Alpha

Teradata’s ClearScape Analytics Enhancements Will Speed up AI Projects & Lower Costs
18 September 2024, insideBIGDATA

Teradata ClearScape Analytics update targets ROI on AI, ML
17 September 2024, TechTarget

Analytics and Data Science News for the Week of September 20; Updates from Firebolt, Qrvey, Teradata & More
20 September 2024, Solutions Review

provided by Google News

Share this page