DBMS > Databend vs. HEAVY.AI vs. Interbase vs. Microsoft SQL Server

System Properties Comparison Databend vs. HEAVY.AI vs. Interbase vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Light-weight proven RDBMS

originally from Borland

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	3.78
Rank	#77	Overall
	#41	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

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

www.embarcadero.com/products/interbase

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

Technical documentation

docs.databend.com

docs.heavy.ai

docs.embarcadero.com/products/interbase

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

Developer

Databend Labs

HEAVY.AI, Inc.

Embarcadero

Microsoft

Initial release

2021

2016

1984

1989

Current release

1.0.59, April 2023

5.10, January 2022

InterBase 2020, December 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++ and CUDA

C++

Server operating systems

hosted
Linux
macOS

Linux

Android
iOS
Linux
OS X
Windows

Linux
Windows

Data scheme

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.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

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

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Interbase Change Views

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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