DBMS > Apache Pinot vs. Dragonfly vs. Postgres-XL vs. SwayDB

System Properties Comparison Apache Pinot vs. Dragonfly vs. Postgres-XL vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

pinot.apache.org

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

www.postgres-xl.org

swaydb.simer.au

Technical documentation

docs.pinot.apache.org

www.dragonflydb.io/docs

www.postgres-xl.org/documentation

Developer

Apache Software Foundation and contributors

DragonflyDB team and community contributors

Simer Plaha

Initial release

2015

2023

2014

since 2012, originally named StormDB

2018

Current release

1.0.0, September 2023

1.0, March 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

Open Source

Mozilla public license

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

C++

Scala

Server operating systems

All OS with a Java JDK11 or higher

Linux

Linux
macOS

Data scheme

yes

scheme-free

yes

schema-free

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Go
Java
Python

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

MVCC

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

fine grained access rights according to SQL-standard

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