DBMS > NSDb vs. OrigoDB vs. YTsaurus

System Properties Comparison NSDb vs. OrigoDB vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Document store
Key-value store

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.11
Rank	#340	Overall
	#45	Document stores
	#50	Key-value stores

Website

nsdb.io

origodb.com

ytsaurus.tech

Technical documentation

nsdb.io/Architecture

origodb.com/docs

ytsaurus.tech/docs/en

Developer

Robert Friberg et al

Yandex

Initial release

2017

2009

under the name LiveDB

2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

C++

Server operating systems

Linux
macOS

Linux
Windows

Ubuntu

Data scheme

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

YQL, an SQL-based language, is supported

APIs and other access methods

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

Java
Scala

.Net

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

depending on model

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

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

Access Control Lists

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