DBMS > EXASOL vs. GridGain vs. Snowflake vs. SWC-DB vs. TDengine

System Properties Comparison EXASOL vs. GridGain vs. Snowflake vs. SWC-DB vs. TDengine

Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

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

A high performance, scalable Wide Column DBMS

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

www.exasol.com

www.gridgain.com

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

github.com/taosdata/TDengine
tdengine.com

Technical documentation

www.exasol.com/resources

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Exasol

GridGain Systems, Inc.

Snowflake Computing Inc.

Alex Kashirin

TDEngine, previously Taos Data

Initial release

2000

2007

2014

2020

2019

Current release

GridGain 8.5.1

0.5, April 2021

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3

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

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux

Linux
Windows

Data scheme

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-like query language

Standard SQL with extensions for time-series applications

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

JDBC
RESTful HTTP API

Supported programming languages

Java
Lua
Python
R

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C++

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

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

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 (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes (compute grid and hadoop accelerator)

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

User concepts

Access control

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

Security Hooks for custom implementations

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...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

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

Streamlining Time-Series Data Management with TDengine’s PostgreSQL Connector
12 June 2024

Enhancing IoT and Industrial Data Management with TDengine’s MySQL Connector
12 June 2024

Comprehensive Comparison Between TDengine and MongoDB
6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

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.