DBMS > IRONdb vs. Machbase Neo vs. Microsoft Azure SQL Database vs. RavenDB vs. VoltDB

System Properties Comparison IRONdb vs. Machbase Neo vs. Microsoft Azure SQL Database vs. RavenDB vs. VoltDB

Editorial information provided by DB-Engines

Name

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

Description

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

TimeSeries DBMS for AIoT and BigData

Database as a Service offering with high compatibility to Microsoft SQL Server

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

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

machbase.com

azure.microsoft.com/en-us/products/azure-sql/database

ravendb.net

www.voltdb.com

Technical documentation

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

machbase.com/dbms

docs.microsoft.com/en-us/azure/azure-sql

ravendb.net/docs

docs.voltdb.com

Developer

Circonus LLC.

Machbase

Microsoft

Hibernating Rhinos

VoltDB Inc.

Initial release

2017

2013

2010

Current release

V0.10.20, January 2018

V8.0, August 2023

V12

5.4, July 2022

11.3, April 2022

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

AGPL version 3, commercial license available

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Java, C++

Server operating systems

Linux

Linux
macOS
Windows

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

SQL-like query language

yes

SQL-like query language (RQL)

yes

only a subset of SQL 99

APIs and other access methods

HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

Transact SQL

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

selectable replication factor

yes, with always 3 replicas available

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

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

volatile and lookup table

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

Users and roles with access to stored procedures

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