DBMS > Graphite vs. ObjectBox vs. RDF4J vs. Splice Machine

System Properties Comparison Graphite vs. ObjectBox vs. RDF4J vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Time Series DBMS

Object oriented DBMS
Vector DBMS

RDF store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

github.com/graphite-project/graphite-web

github.com/objectbox
objectbox.io

rdf4j.org

splicemachine.com

Technical documentation

graphite.readthedocs.io

docs.objectbox.io

rdf4j.org/documentation

splicemachine.com/how-it-works

Developer

Chris Davis

ObjectBox Limited

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

Splice Machine

Initial release

2006

2017

2004

2014

Current release

4.0 (May 2024)

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL 3.0, commercial license available

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

Python

C and C++

Java

Server operating systems

Linux
Unix

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

Numeric data only

yes, plus "flex" map-like 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

yes

APIs and other access methods

HTTP API
Sockets

Proprietary native API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript (Node.js)
Python

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Java
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Data sync between devices allowing occasional connected databases to work completely offline

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

yes

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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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

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

Most Prominent Time Series Databases For Data Scientists
6 September 2021, AIM

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

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Hadoop is not a static data repository, says Splice Machine CEO | #BigDataSV
12 February 2014, SiliconANGLE News

provided by Google News

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