DBMS > HEAVY.AI vs. Heroic vs. Microsoft SQL Server vs. TDengine vs. Transwarp Hippo

System Properties Comparison HEAVY.AI vs. Heroic vs. Microsoft SQL Server vs. TDengine vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Microsofts flagship relational DBMS

Time Series DBMS and big data platform

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

github.com/spotify/heroic

www.microsoft.com/en-us/sql-server

github.com/taosdata/TDengine
tdengine.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.heavy.ai

spotify.github.io/heroic

learn.microsoft.com/en-US/sql/sql-server

docs.tdengine.com

Developer

HEAVY.AI, Inc.

Spotify

Microsoft

TDEngine, previously Taos Data

Initial release

2016

2014

1989

2019

2023

Current release

5.10, January 2022

SQL Server 2022, November 2022

3.0, August 2022

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

AGPL V3, also commercial editions 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.

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Implementation language

C++ and CUDA

Java

C++

Server operating systems

Linux

Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

via Elasticsearch

yes

SQL

Support of SQL

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
Thrift
Vega

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

C++
Java
Python

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

fine grained access rights according to SQL-standard

yes

Role based access control and fine grained access rights

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

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