DBMS > Dragonfly vs. GeoMesa vs. Greenplum vs. OrientDB vs. SAP HANA

System Properties Comparison Dragonfly vs. GeoMesa vs. Greenplum vs. OrientDB vs. SAP HANA

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Multi-model DBMS (Document, Graph, Key/Value)

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

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

www.geomesa.org

greenplum.org

orientdb.org

www.sap.com/products/hana.html

Technical documentation

www.dragonflydb.io/docs

www.geomesa.org/documentation/stable/user/index.html

docs.greenplum.org

www.orientdb.com/docs/last/index.html

help.sap.com/hana

Developer

DragonflyDB team and community contributors

CCRi and others

Pivotal Software Inc.

OrientDB LTD; CallidusCloud; SAP

SAP

Initial release

2023

2014

2005

2010

Current release

1.0, March 2023

5.0.0, May 2024

7.0.0, September 2023

3.2.29, March 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Scala

Java

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

Appliance or cloud-service

Data scheme

scheme-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

JDBC
ODBC

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
Perl
Python
R

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

Server-side scripts

Stored procedures

Lua

yes

Java, Javascript

SQLScript, R

Triggers

publish/subscribe channels provide some trigger functionality

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

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

depending on storage layer

yes

User concepts

Access control

Password-based authentication

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

yes

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