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

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

Please select another system to include it in the comparison.

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

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

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

pinot.apache.org

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

hughestech.com.au/products/msql

www.postgres-xl.org

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

Hughes Technologies

Initial release

2015

2023

1994

2014

since 2012, originally named StormDB

Current release

1.0.0, September 2023

1.0, March 2023

4.4, October 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSL 1.1

commercial

free licenses can be provided

Open Source

Mozilla public license

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++

Server operating systems

All OS with a Java JDK11 or higher

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

yes

scheme-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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

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

horizontal partitioning

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

none

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

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, businesswire.com

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Intel Linux Kernel Optimizations Show Huge Benefit For High Core Count Servers
29 March 2023, Phoronix

SFU Computing Science researchers receive 2022 ACM SIGMOD Research Highlight Award.
24 February 2023, Simon Fraser University News

provided by Google News

Higher Education PS rules out ghost students before PAC
29 November 2018, diggers.news

provided by Google News

Share this page