DBMS > Databend vs. HyperSQL vs. KairosDB vs. Sequoiadb

System Properties Comparison Databend vs. HyperSQL vs. KairosDB 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

Distributed Time Series DBMS based on Cassandra or H2

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

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

hsqldb.org

github.com/kairosdb/kairosdb

www.sequoiadb.com

Technical documentation

docs.databend.com

hsqldb.org/web/hsqlDocsFrame.html

kairosdb.github.io

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

Developer

Databend Labs

Sequoiadb Ltd.

Initial release

2021

2001

2013

Current release

1.0.59, April 2023

2.7.2, June 2023

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache 2.0

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++

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

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

Linux
OS X
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

Graphite protocol
HTTP REST
Telnet API

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC
Java

Java
JavaScript

Node.js
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

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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