DBMS > HEAVY.AI vs. Microsoft SQL Server vs. Newts vs. Sadas Engine vs. SingleStore

System Properties Comparison HEAVY.AI vs. Microsoft SQL Server vs. Newts vs. Sadas Engine vs. SingleStore

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

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	4.02
Rank	#74	Overall
	#39	Relational DBMS

Website

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

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

opennms.github.io/newts

www.sadasengine.com

www.singlestore.com

Technical documentation

docs.heavy.ai

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

github.com/OpenNMS/newts/wiki

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

docs.singlestore.com

Developer

HEAVY.AI, Inc.

Microsoft

OpenNMS Group

SADAS s.r.l.

SingleStore Inc.

Initial release

2016

1989

2014

2006

2013

Current release

5.10, January 2022

SQL Server 2022, November 2022

8.0

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

free trial version available

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C++

Java

C++

C++, Go

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

AIX
Linux
Windows

Linux

64 bit version required

Data scheme

yes

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

but no triggers and foreign keys

APIs and other access methods

JDBC
ODBC
Thrift
Vega

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

HTTP REST
Java API

JDBC
ODBC
Proprietary protocol

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

Java

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

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

Sharding

based on Cassandra

horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

selectable replication factor

based on Cassandra

none

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Fine grained access control via users, groups and roles

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