DBMS > Hyprcubd vs. Kinetica vs. RisingWave vs. SAP HANA

System Properties Comparison Hyprcubd vs. Kinetica vs. RisingWave vs. SAP HANA

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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

Fully vectorized database across both GPUs and CPUs

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

hyprcubd.com (offline)

www.kinetica.com

www.risingwave.com/database

www.sap.com/products/hana.html

Technical documentation

docs.kinetica.com

docs.risingwave.com/docs/current/intro

help.sap.com/hana

Developer

Hyprcubd, Inc.

Kinetica

RisingWave Labs

SAP

Initial release

2012

2022

2010

Current release

7.1, August 2021

1.2, September 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++

Rust

Server operating systems

hosted

Linux

Docker
Linux
macOS

Appliance or cloud-service

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

Standard SQL-types and JSON

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC (https)

JDBC
ODBC
RESTful HTTP API

JDBC
PostgreSQL wire protocol

JDBC
ODBC

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

UDFs in Python or Java

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

token access

Access rights for users and roles on table level

Users and Roles

yes

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