DBMS > Dragonfly vs. LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage vs. RocksDB

System Properties Comparison Dragonfly vs. LeanXcale vs. Microsoft Access vs. Microsoft Azure Table Storage vs. RocksDB

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A Wide Column Store for rapid development using massive semi-structured datasets

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

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Wide column store

Key-value store

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

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

www.leanxcale.com

www.microsoft.com/en-us/microsoft-365/access

azure.microsoft.com/en-us/services/storage/tables

rocksdb.org

Technical documentation

www.dragonflydb.io/docs

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

Developer

DragonflyDB team and community contributors

LeanXcale

Microsoft

Facebook, Inc.

Initial release

2023

2015

1992

2012

2013

Current release

1.0, March 2023

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Bundled with Microsoft Office

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

Windows

Not a real database server, but making use of DLLs

hosted

Linux

Data scheme

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

through Apache Derby

yes

but not compliant to any SQL standard

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

C++ API
Java 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
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

since Access 2010 using the ACE-engine

Triggers

publish/subscribe channels provide some trigger functionality

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

but no files for transaction logging

optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

a simple user-level security was built in till version Access 2003

Access rights based on private key authentication or shared access signatures

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