DBMS > Dragonfly vs. Elasticsearch vs. RocksDB vs. Spark SQL vs. Stardog

System Properties Comparison Dragonfly vs. Elasticsearch vs. RocksDB vs. Spark SQL vs. Stardog

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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

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

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

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

www.elastic.co/elasticsearch

rocksdb.org

spark.apache.org/sql

www.stardog.com

Technical documentation

www.dragonflydb.io/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

Developer

DragonflyDB team and community contributors

Elastic

Facebook, Inc.

Apache Software Foundation

Stardog-Union

Initial release

2023

2010

2013

2014

2010

Current release

1.0, March 2023

8.6, January 2023

9.2.1, May 2024

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Elastic License

Open Source

BSD

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Scala

Java

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

scheme-free

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Java API
RESTful HTTP/JSON API

C++ API
Java API

JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

by using the 'percolation' feature

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Atomic execution of command blocks and scripts

yes

ACID

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

Memcached and Redis integration

yes

User concepts

Access control

Password-based authentication

Access rights for users and roles

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