DBMS > Bangdb vs. H2 vs. Microsoft Azure Synapse Analytics

System Properties Comparison Bangdb vs. H2 vs. Microsoft Azure Synapse Analytics

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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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Website

bangdb.com

www.h2database.com

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.bangdb.com

www.h2database.com/html/main.html

docs.microsoft.com/azure/synapse-analytics

Developer

Sachin Sinha, BangDB

Thomas Mueller

Microsoft

Initial release

2012

2005

2016

Current release

BangDB 2.0, October 2021

2.2.220, July 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

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

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

Java

C#
Java
PHP

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Transact SQL

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

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

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

Foreign keys

Referential integrity

yes

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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)

fine grained access rights according to SQL-standard

yes

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