DBMS > Apache Drill vs. Dragonfly vs. Microsoft Azure Synapse Analytics vs. RocksDB

System Properties Comparison Apache Drill vs. Dragonfly vs. Microsoft Azure Synapse Analytics vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key-value store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

drill.apache.org

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

azure.microsoft.com/services/synapse-analytics

rocksdb.org

Technical documentation

drill.apache.org/docs

www.dragonflydb.io/docs

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

DragonflyDB team and community contributors

Microsoft

Facebook, Inc.

Initial release

2012

2023

2016

2013

Current release

1.20.3, January 2023

1.0, March 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSL 1.1

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

C++

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
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Lua

Transact SQL

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Password-based authentication

yes

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