DBMS > FeatureBase vs. NSDb vs. OrigoDB vs. OushuDB

System Properties Comparison FeatureBase vs. NSDb vs. OrigoDB vs. OushuDB

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

A fully ACID in-memory object graph database

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

www.featurebase.com

nsdb.io

origodb.com

www.oushu.com/product/oushuDB

Technical documentation

docs.featurebase.com

nsdb.io/Architecture

origodb.com/docs

www.oushu.com/documentation

Developer

Molecula and Pilosa Open Source Contributors

Robert Friberg et al

Oushu

Initial release

2017

2009

under the name LiveDB

Current release

2022, May 2022

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

commercial

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, Scala

Server operating systems

Linux
macOS

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

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 queries

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

Java
Python

Java
Scala

.Net

C
C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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

Kerberos, SSL and role based access

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More resources

Recent citations in the news

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