DBMS > Bangdb vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Sequoiadb

System Properties Comparison Bangdb vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

bangdb.com

www.graphengine.io

azure.microsoft.com/services/synapse-analytics

www.sequoiadb.com

Technical documentation

docs.bangdb.com

www.graphengine.io/docs/manual

docs.microsoft.com/azure/synapse-analytics

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Sachin Sinha, BangDB

Microsoft

Sequoiadb Ltd.

Initial release

2012

2010

2016

2013

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

.NET and C

C++

Server operating systems

Linux

.NET

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

C
C#
C++
Java
Python

C#
C++
F#
Visual Basic

C#
Java
PHP

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transact SQL

JavaScript

Triggers

yes, Notifications (with Streaming only)

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

horizontal partitioning

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

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

Immediate Consistency

Eventual 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

Document is locked during a transaction

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

User concepts

Access control

yes (enterprise version only)

yes

simple password-based access control

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