DBMS > Apache Kylin vs. Datomic vs. IRONdb vs. NSDb

System Properties Comparison Apache Kylin vs. Datomic vs. IRONdb vs. NSDb

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Editorial information provided by DB-Engines

Name

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

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

Time Series DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

kylin.apache.org

www.datomic.com

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

nsdb.io

Technical documentation

kylin.apache.org/docs

docs.datomic.com

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

nsdb.io/Architecture

Developer

Apache Software Foundation, originally contributed from eBay Inc

Cognitect

Circonus LLC.

Initial release

2015

2012

2017

Current release

3.1.0, July 2020

1.0.6735, June 2023

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

commercial

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

Java, Clojure

C and C++

Java, Scala

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

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

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

Clojure
Java

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

Java
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in Lua

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Using Apache Lucene

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

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More resources

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