DBMS > Apache Druid vs. Databend vs. Linter vs. OpenQM vs. SwayDB

System Properties Comparison Apache Druid vs. Databend vs. Linter vs. OpenQM vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

RDBMS for high security requirements

QpenQM is a high-performance, self-tuning, multi-value DBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Multivalue DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

druid.apache.org

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

linter.ru

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

swaydb.simer.au

Technical documentation

druid.apache.org/docs/latest/design

docs.databend.com

Developer

Apache Software Foundation and contributors

Databend Labs

relex.ru

Rocket Software, originally Martin Phillips

Simer Plaha

Initial release

2012

2021

1990

1993

2018

Current release

29.0.1, April 2024

1.0.59, April 2023

3.4-12

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GNU Affero GPL V3.0

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

Java

Rust

C and C++

Scala

Server operating systems

Linux
OS X
Unix

hosted
Linux
macOS

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-less columns are supported

yes

with some exceptions

schema-free

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

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

yes

none

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

Atomic execution of operations

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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