DBMS > Geode vs. Hawkular Metrics vs. InfluxDB vs. Ingres vs. RocksDB

System Properties Comparison Geode vs. Hawkular Metrics vs. InfluxDB vs. Ingres vs. RocksDB

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

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

DBMS for storing time series, events and metrics

Well established RDBMS

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

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.99
Rank	#133	Overall
	#23	Key-value stores

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	4.67
Rank	#77	Overall
	#42	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

geode.apache.org

www.hawkular.org

www.influxdata.com/products/influxdb-overview

www.actian.com/databases/ingres

rocksdb.org

Technical documentation

geode.apache.org/docs

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

docs.influxdata.com/influxdb

docs.actian.com/ingres

github.com/facebook/rocksdb/wiki

Developer

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

Community supported by Red Hat

Actian Corporation

Facebook, Inc.

Initial release

2002

2014

2013

1974

originally developed at University Berkely in early 1970s

2013

Current release

1.1, February 2017

2.7.5, January 2024

11.2, May 2022

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

BSD

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

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

Linux
OS X

through Homebrew

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

SQL-like query language

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

HTTP REST

HTTP API
JSON over UDP

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

C++ API
Java API

Supported programming languages

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

Go
Java
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

in enterprise version only

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

selectable replication factor

in enterprise version only

Ingres Replicator

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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 used storage engine

yes

User concepts

Access control

Access rights per client and object definable

simple rights management via user accounts

fine grained access rights according to SQL-standard

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