DBMS > Hyprcubd vs. NSDb vs. RisingWave

System Properties Comparison Hyprcubd vs. NSDb vs. RisingWave

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Serverless Time Series DBMS

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

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

hyprcubd.com (offline)

nsdb.io

www.risingwave.com/database

Technical documentation

nsdb.io/Architecture

docs.risingwave.com/docs/current/intro

Developer

Hyprcubd, Inc.

RisingWave Labs

Initial release

2017

2022

Current release

1.2, September 2023

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

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Scala

Rust

Server operating systems

hosted

Linux
macOS

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes: int, bigint, decimal, string

Standard SQL-types and JSON

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 (https)

gRPC
HTTP REST
WebSocket

JDBC
PostgreSQL wire protocol

Supported programming languages

Java
Scala

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

UDFs in Python or Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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.

yes

User concepts

Access control

token access

Users and Roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Streaming Databases: Embracing the Convergence of Stream Processing and Databases
17 May 2024, InfoQ.com

RisingWave Cloud Democratizes Event Stream Processing, Making It Affordable at Cloud Scale
27 June 2023, Datanami

Ibis 8 Adds Streaming
5 March 2024, iProgrammer

Building a Formula 1 Streaming Data Pipeline With Kafka and Risingwave
5 September 2023, KDnuggets

As the world ages, cancer cases are projected to rise, hitting some countries like ‘a tidal wave’
4 April 2024, CNN

provided by Google News

Share this page