DBMS > Blueflood vs. IRONdb vs. RDF4J vs. RisingWave

System Properties Comparison Blueflood vs. IRONdb vs. RDF4J vs. RisingWave

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Time Series DBMS

RDF store

Relational DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

blueflood.io

www.circonus.com/solutions/time-series-database/

rdf4j.org

www.risingwave.com/database

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.circonus.com/irondb/category/getting-started

rdf4j.org/documentation

docs.risingwave.com/docs/current/intro

Developer

Rackspace

Circonus LLC.

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

RisingWave Labs

Initial release

2013

2017

2004

2022

Current release

V0.10.20, January 2018

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 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

C and C++

Java

Rust

Server operating systems

Linux
OS X

Linux

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

predefined scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

Standard SQL-types and JSON

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 (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

HTTP REST

HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
PostgreSQL wire protocol

Supported programming languages

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

Java
PHP
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, in Lua

yes

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

configurable replication factor, datacenter aware

none

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 per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

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

Users and Roles

More information provided by the system vendor

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

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

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

provided by Google News

Streaming Databases: Embracing the Convergence of Stream Processing and Databases
17 May 2024, InfoQ.com

RisingWave Cloud Democratizes Event Stream Processing, Making It Affordable at Cloud Scale
27 June 2023, Datanami

Ibis 8 Adds Streaming
5 March 2024, iProgrammer

Building a Formula 1 Streaming Data Pipeline With Kafka and Risingwave
5 September 2023, KDnuggets

Open Source Ibis 8.0 Lets Data Teams Write Code Once and Use Across Local, Batch and Streaming Query Engines ...
12 February 2024, GlobeNewswire

provided by Google News

Share this page