DBMS > BigObject vs. Geode vs. GraphDB vs. Hawkular Metrics

System Properties Comparison BigObject vs. Geode vs. GraphDB vs. Hawkular Metrics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Graph DBMS
RDF store

Time Series DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Score	2.76
Rank	#99	Overall
	#8	Graph DBMS
	#4	RDF stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Website

Technical documentation

docs.bigobject.io

geode.apache.org/docs

graphdb.ontotext.com/documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

Social network pages

Developer

BigObject, Inc.

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

Ontotext

Community supported by Red Hat

Initial release

2015

2002

2000

2014

Current release

1.1, February 2017

10.4, October 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache 2.0

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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

the JDK (8 or later) is also required

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

Typing

predefined data types such as float or date

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

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (OQL)

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

HTTP REST

Supported programming languages

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

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

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Constraint checking

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights per client and object definable

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

This is how much one of the most expensive gems costs at the Tucson gem show
11 February 2024, KGUN 9 Tucson News

Apache Geode Spawns ‘All Sorts of In-Memory Things’
4 January 2017, The New Stack

RDBMS and Apache Geode Data Movement: Low Latency ETL Pipeline by Using Cloud-Native Event Driven Microservices
30 June 2018, InfoQ.com

Chapter 1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode
15 November 2018, O'Reilly Media

HPE buys query acceleration platform Ampool to boost Ezmeral hybrid cloud analytics
7 July 2021, SiliconANGLE News

provided by Google News

Ontotext’s GraphDB Solution Now Available on the Microsoft Azure Marketplace
17 January 2024, Datanami

Ontotext's GraphDB Solution Now Available in the AWS Marketplace
9 October 2023, PR Newswire

Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
18 December 2019, KDnuggets

Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations
5 July 2022, PR Newswire

Knowledge graphs change the nature of business intelligence
8 April 2024, TechHQ

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Share this page