DBMS > Dragonfly vs. Microsoft Azure Cosmos DB vs. PostGIS vs. SAP SQL Anywhere vs. Splunk

System Properties Comparison Dragonfly vs. Microsoft Azure Cosmos DB vs. PostGIS vs. SAP SQL Anywhere vs. Splunk

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

Globally distributed, horizontally scalable, multi-model database service

Spatial extension of PostgreSQL

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Analytics Platform for Big Data

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Spatial DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

Relational DBMS

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

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

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

azure.microsoft.com/services/cosmos-db

postgis.net

www.sap.com/products/technology-platform/sql-anywhere.html

www.splunk.com

Technical documentation

www.dragonflydb.io/docs

learn.microsoft.com/azure/cosmos-db

postgis.net/documentation

help.sap.com/docs/SAP_SQL_Anywhere

docs.splunk.com/Documentation/Splunk

Developer

DragonflyDB team and community contributors

Microsoft

SAP

formerly Sybase

Splunk Inc.

Initial release

2023

2014

2005

1992

2003

Current release

1.0, March 2023

3.4.2, February 2024

17, July 2015

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

GPL v2.0

commercial

Limited free edition and free developer edition available

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

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

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

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

Splunk Search Processing Language for search commands

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
HTTP API
JDBC
ODBC

HTTP REST

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

JavaScript

user defined functions

yes, in C/C++, Java, .Net or Perl

yes

Triggers

publish/subscribe channels provide some trigger functionality

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

based on PostgreSQL

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

based on PostgreSQL

Source-replica replication

Database mirroring

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual 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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

Access rights can be defined down to the item level

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

Access rights for users and roles

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