DBMS > GigaSpaces vs. Hyprcubd vs. Microsoft Azure Synapse Analytics vs. NSDb vs. WakandaDB

System Properties Comparison GigaSpaces vs. Hyprcubd vs. Microsoft Azure Synapse Analytics vs. NSDb vs. WakandaDB

Editorial information provided by DB-Engines

Name

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

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Serverless Time Series DBMS

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

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Graph DBMS
Search engine

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

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.gigaspaces.com

hyprcubd.com (offline)

azure.microsoft.com/services/synapse-analytics

nsdb.io

wakanda.github.io

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

wakanda.github.io/doc

Developer

Gigaspaces Technologies

Hyprcubd, Inc.

Microsoft

Wakanda SAS

Initial release

2000

2016

2017

2012

Current release

15.5, September 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

Apache Version 2.0

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

Java, C++, .Net

C++

Java, Scala

C++, JavaScript

Server operating systems

Linux
macOS
Solaris
Windows

hosted

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

yes

SQL-like query language

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

gRPC (https)

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

.Net
C++
Java
Python
Scala

C#
Java
PHP

Java
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Transact SQL

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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.

yes

User concepts

Access control

Role-based access control

token access

yes

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