DBMS > InfinityDB vs. IRONdb vs. Transbase vs. VelocityDB vs. XTDB

System Properties Comparison InfinityDB vs. IRONdb vs. Transbase vs. VelocityDB vs. XTDB

Editorial information provided by DB-Engines

Name

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

Description

A Java embedded Key-Value Store which extends the Java Map interface

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

A resource-optimized, high-performance, universally applicable RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Document store

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

boilerbay.com

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

www.transaction.de/en/products/transbase.html

velocitydb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

boilerbay.com/infinitydb/manual

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

www.transaction.de/en/products/transbase/features.html

velocitydb.com/UserGuide

www.xtdb.com/docs

Developer

Boiler Bay Inc.

Circonus LLC.

Transaction Software GmbH

VelocityDB Inc

Juxt Ltd.

Initial release

2002

2017

1987

2011

2019

Current release

4.0

V0.10.20, January 2018

Transbase 8.3, 2022

7.x

1.19, September 2021

License

Commercial or Open Source

commercial

free development license

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

All OS with a Java VM

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

text, numeric, histograms

yes

yes, extensible-data-notation format

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

HTTP REST
JDBC

Supported programming languages

Java

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

.Net

Clojure
Java

Server-side scripts

Stored procedures

yes, in Lua

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic, metric affinity per node

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Based on Windows Authentication

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

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

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

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

provided by Google News

Share this page