DBMS > Databricks vs. EXASOL vs. InfinityDB vs. Snowflake vs. TDengine

System Properties Comparison Databricks vs. EXASOL vs. InfinityDB vs. Snowflake vs. TDengine

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

A Java embedded Key-Value Store which extends the Java Map interface

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

Time Series DBMS and big data platform

Primary database model

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.databricks.com

www.exasol.com/resources

boilerbay.com/infinitydb/manual

docs.snowflake.net/manuals/index.html

docs.tdengine.com

Developer

Databricks

Exasol

Boiler Bay Inc.

Snowflake Computing Inc.

TDEngine, previously Taos Data

Initial release

2013

2000

2002

2014

2019

Current release

4.0

3.0, August 2022

License

Commercial or Open Source

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

Java

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

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

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

with Databricks SQL

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

Python
R
Scala

Java
Lua
Python
R

Java

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions and aggregates

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

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

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

yes

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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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...
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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

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