DBMS > Apache Kylin vs. Dragonfly vs. DuckDB vs. Hypertable vs. VoltDB

System Properties Comparison Apache Kylin vs. Dragonfly vs. DuckDB vs. Hypertable vs. VoltDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

An embeddable, in-process, column-oriented SQL OLAP RDBMS

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

kylin.apache.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

duckdb.org

www.voltdb.com

Technical documentation

kylin.apache.org/docs

www.dragonflydb.io/docs

duckdb.org/docs

docs.voltdb.com

Developer

Apache Software Foundation, originally contributed from eBay Inc

DragonflyDB team and community contributors

Hypertable Inc.

VoltDB Inc.

Initial release

2015

2023

2018

2009

2010

Current release

3.1.0, July 2020

1.0, March 2023

1.0.0, June 2024

0.9.8.11, March 2016

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++

Java, C++

Server operating systems

Linux

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

for development

Data scheme

yes

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

C++ API
Thrift

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C++
Java
Perl
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

Java

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor on file system level

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Password-based authentication

Users and roles with access to stored procedures

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