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

System Properties Comparison Bangdb 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

Converged and high performance database for device data, events, time series, document and graph

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
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series 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

bangdb.com

hyprcubd.com (offline)

azure.microsoft.com/services/synapse-analytics

nsdb.io

wakanda.github.io

Technical documentation

docs.bangdb.com

docs.microsoft.com/azure/synapse-analytics

nsdb.io/Architecture

wakanda.github.io/doc

Developer

Sachin Sinha, BangDB

Hyprcubd, Inc.

Microsoft

Wakanda SAS

Initial release

2012

2016

2017

2012

Current release

BangDB 2.0, October 2021

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

BSD 3

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

C, C++

C++

Java, Scala

C++, JavaScript

Server operating systems

Linux

hosted

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

gRPC (https)

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

C#
Java
PHP

Java
Scala

JavaScript

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

token access

yes

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