DBMS > Hyprcubd vs. Microsoft Azure Synapse Analytics vs. NSDb vs. TDSQL for MySQL vs. WakandaDB

System Properties Comparison Hyprcubd vs. Microsoft Azure Synapse Analytics vs. NSDb vs. TDSQL for MySQL vs. WakandaDB

Editorial information provided by DB-Engines

Name

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

Description

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

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Spatial DBMS

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	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

hyprcubd.com (offline)

azure.microsoft.com/services/synapse-analytics

nsdb.io

www.tencentcloud.com/products/dcdb

wakanda.github.io

Technical documentation

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

www.tencentcloud.com/document/product/1042

wakanda.github.io/doc

Developer

Hyprcubd, Inc.

Microsoft

Tencent

Wakanda SAS

Initial release

2016

2017

2013

2012

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

AGPLv3, extended 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

C++, JavaScript

Server operating systems

hosted

Linux
macOS

hosted

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

APIs and other access methods

gRPC (https)

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
Java
PHP

Java
Scala

C
C#
C++
Java
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

Immediate Consistency

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

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

token access

yes

Users with fine-grained authorization concept

yes

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