DBMS > NSDb vs. SWC-DB vs. Transbase vs. Transwarp Hippo

System Properties Comparison NSDb vs. SWC-DB vs. Transbase vs. Transwarp Hippo

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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 high performance, scalable Wide Column DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Website

nsdb.io

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transaction.de/en/products/transbase.html

www.transwarp.cn/en/subproduct/hippo

Technical documentation

nsdb.io/Architecture

www.transaction.de/en/products/transbase/features.html

Developer

Alex Kashirin

Transaction Software GmbH

Initial release

2017

2020

1987

2023

Current release

0.5, April 2021

Transbase 8.3, 2022

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPL V3

commercial

free development license

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

C++

C and C++

C++

Server operating systems

Linux
macOS

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

yes

Vector, Numeric and 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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

Java
Scala

C++

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Role based access control and fine grained access rights

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