DBMS > Databend vs. HyperSQL vs. SAP Adaptive Server vs. Sequoiadb

System Properties Comparison Databend vs. HyperSQL vs. SAP Adaptive Server vs. Sequoiadb

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

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

hsqldb.org

www.sap.com/products/technology-platform/sybase-ase.html

www.sequoiadb.com

Technical documentation

docs.databend.com

hsqldb.org/web/hsqlDocsFrame.html

help.sap.com/docs/SAP_ASE

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Databend Labs

SAP, Sybase

Sequoiadb Ltd.

Initial release

2021

2001

1987

2013

Current release

1.0.59, April 2023

2.7.2, June 2023

16.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

based on BSD license

commercial

Open Source

Server: AGPL; Client: Apache V2

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.

Implementation language

Rust

Java

C and C++

C++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

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

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC
Java

C
C++
Cobol
Java
Java
Perl
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

Java and Transact-SQL

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Document is locked during a transaction

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

simple password-based access control

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