DBMS > Graph Engine vs. Graphite vs. Oracle Rdb vs. VoltDB

System Properties Comparison Graph Engine vs. Graphite vs. Oracle Rdb vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

www.graphengine.io

github.com/graphite-project/graphite-web

www.oracle.com/database/technologies/related/rdb.html

www.voltdb.com

Technical documentation

www.graphengine.io/docs/manual

graphite.readthedocs.io

www.oracle.com/database/technologies/related/rdb-doc.html

docs.voltdb.com

Developer

Microsoft

Chris Davis

Oracle, originally developed by Digital Equipment Corporation (DEC)

VoltDB Inc.

Initial release

2010

2006

1984

2010

Current release

7.4.1.1, 2021

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

.NET and C

Python

Java, C++

Server operating systems

.NET

Linux
Unix

HP Open VMS

Linux
OS X

for development

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

HTTP API
Sockets

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes, on a single node

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019
27 February 2019, Data Science Central

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Collecting, storing, and analyzing your DevOps workloads with open-source Telegraf, Amazon Timestream, and Grafana
25 November 2020, AWS Blog

provided by Google News

Oracle Adds New AI-Enabling Features To MySQL HeatWave
23 March 2023, Forbes

Oracle Business Model
13 June 2023, Business Model Analyst

2013 Data Science Salary Survey
4 May 2013, O'Reilly Media

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

Unveiling Volt Active Data’s game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Aims for Fast Big Data Development
29 January 2015, ADT Magazine

VoltDB Announces Key New Hires
26 October 2021, citybiz

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

provided by Google News

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