DBMS > Geode vs. HarperDB vs. RDF4J vs. SAP HANA vs. SwayDB

System Properties Comparison Geode vs. HarperDB vs. RDF4J vs. SAP HANA vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

geode.apache.org

www.harperdb.io

rdf4j.org

www.sap.com/products/hana.html

swaydb.simer.au

Technical documentation

geode.apache.org/docs

docs.harperdb.io/docs

rdf4j.org/documentation

help.sap.com/hana

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

HarperDB

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

SAP

Simer Plaha

Initial release

2002

2017

2004

2010

2018

Current release

1.1, February 2017

3.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

free community edition available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

GNU Affero GPL V3.0

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

Java

Node.js

Java

Scala

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

schema-free

dynamic schema

yes

RDF Schemas

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

SQL-like data manipulation statements

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

Custom Functions

since release 3.1

yes

SQLScript, R

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

the nodes on which a table resides can be defined

none

yes

none

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

yes, on a single node

Atomic execution of specific operations

ACID

Isolation support depends on the API used

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

in-memory storage is supported as well

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

Access rights per client and object definable

Access rights for users and roles

yes

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