DBMS > JaguarDB vs. NSDb vs. STSdb vs. Transwarp StellarDB

System Properties Comparison JaguarDB vs. NSDb vs. STSdb vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Key-value store
Vector DBMS

Time Series DBMS

Key-value store

Graph DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Website

www.jaguardb.com

nsdb.io

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/stellardb

Technical documentation

www.jaguardb.com/support.html

nsdb.io/Architecture

Developer

DataJaguar, Inc.

STS Soft SC

Transwarp

Initial release

2015

2017

2011

Current release

3.3 July 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

Java, Scala

Server operating systems

Linux

Linux
macOS

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

primitive types and user defined types (classes)

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API

OpenCypher

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
Scala

C#
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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.

User concepts

Access control

rights management via user accounts

yes

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