DBMS > IRONdb vs. Linter vs. NSDb vs. Qdrant

System Properties Comparison IRONdb vs. Linter vs. NSDb vs. Qdrant

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

RDBMS for high security requirements

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

A high-performance vector database with neural network or semantic-based matching

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

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

linter.ru

nsdb.io

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

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

nsdb.io/Architecture

qdrant.tech/documentation

Developer

Circonus LLC.

relex.ru

Qdrant

Initial release

2017

1990

2017

2021

Current release

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

C and C++

Java, Scala

Rust

Server operating systems

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

yes: int, bigint, decimal, string

Numbers, Strings, Geo, Boolean

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

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

yes

SQL-like query language

APIs and other access methods

HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

gRPC
HTTP REST
WebSocket

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Java
Scala

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes, in Lua

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

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 Apache Lucene

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

fine grained access rights according to SQL-standard

Key-based authentication

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More resources

Recent citations in the news

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