DBMS > Hyprcubd vs. Microsoft Azure Synapse Analytics vs. Newts vs. Spark SQL vs. STSdb

System Properties Comparison Hyprcubd vs. Microsoft Azure Synapse Analytics vs. Newts vs. Spark SQL vs. STSdb

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Time Series DBMS based on Cassandra

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

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

Website

hyprcubd.com (offline)

azure.microsoft.com/services/synapse-analytics

opennms.github.io/newts

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

docs.microsoft.com/azure/synapse-analytics

github.com/OpenNMS/newts/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Hyprcubd, Inc.

Microsoft

OpenNMS Group

Apache Software Foundation

STS Soft SC

Initial release

2016

2014

2011

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

C++

Java

Scala

Server operating systems

hosted

Linux
OS X
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, 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

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

gRPC (https)

ADO.NET
JDBC
ODBC

HTTP REST
Java API

JDBC
ODBC

.NET Client API

Supported programming languages

C#
Java
PHP

Java

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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.

User concepts

Access control

token access

yes

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