DBMS > Alibaba Cloud TSDB vs. EsgynDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Alibaba Cloud TSDB vs. EsgynDB vs. Sadas Engine vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.29
Rank	#301	Overall
	#26	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

www.esgyn.cn

www.sadasengine.com

spark.apache.org/sql

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba

Esgyn

SADAS s.r.l.

Apache Software Foundation

Initial release

2015

2006

2014

Current release

8.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

C++

Scala

Server operating systems

hosted

Linux

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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'

User concepts

Access control

Access managed on TSDB instance level

fine grained access rights according to SQL-standard

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

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