DBMS > Dragonfly vs. FeatureBase vs. Microsoft SQL Server vs. Oracle Rdb vs. SAP Advantage Database Server

System Properties Comparison Dragonfly vs. FeatureBase vs. Microsoft SQL Server vs. Oracle Rdb vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Microsofts flagship relational DBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

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

www.featurebase.com

www.microsoft.com/en-us/sql-server

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

www.sap.com/products/advantage-database-server.html

Technical documentation

www.dragonflydb.io/docs

docs.featurebase.com

learn.microsoft.com/en-US/sql/sql-server

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

Developer

DragonflyDB team and community contributors

Molecula and Pilosa Open Source Contributors

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sybase, SAP

Initial release

2023

2017

1989

1984

1993

Current release

1.0, March 2023

2022, May 2022

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Server operating systems

Linux

Linux
macOS

Linux
Windows

HP Open VMS

Linux
Windows

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

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

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

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

Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Delphi
Perl
PHP

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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

yes

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

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