DBMS > Dragonfly vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. SiriDB

System Properties Comparison Dragonfly vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Open Source Time Series DBMS

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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

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

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

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

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/rdb.html

siridb.com

Technical documentation

www.dragonflydb.io/docs

docs.microsoft.com/azure/synapse-analytics

www.oracle.com/database/technologies/related/rdb-doc.html

docs.siridb.com

Developer

DragonflyDB team and community contributors

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Cesbit

Initial release

2023

2016

1984

2017

Current release

1.0, March 2023

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

hosted

HP Open VMS

Linux

Data scheme

scheme-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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

yes

Numeric data

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

HTTP 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#
Java
PHP

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Lua

Transact SQL

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

yes, on a single node

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

yes

simple rights management via user accounts

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