DBMS > Amazon Redshift vs. EXASOL vs. JaguarDB vs. Snowflake vs. TDengine

System Properties Comparison Amazon Redshift vs. EXASOL vs. JaguarDB vs. Snowflake vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

aws.amazon.com/redshift

www.exasol.com

www.jaguardb.com

www.snowflake.com

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Amazon (based on PostgreSQL)

Exasol

DataJaguar, Inc.

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2012

2000

2015

2014

2019

Current release

3.3 July 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

AGPL V3, also commercial editions available

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++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

hosted

Linux
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

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

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

TDengine 3.3.0.0 Release Notes
7 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.