DBMS > Bangdb vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. Trino

System Properties Comparison Bangdb vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. Trino

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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 robust and reliable RDBMS optimized to run all major SAP solutions

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

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

bangdb.com

maxdb.sap.com

azure.microsoft.com/services/synapse-analytics

trino.io

Technical documentation

docs.bangdb.com

maxdb.sap.com/documentation

docs.microsoft.com/azure/synapse-analytics

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Sachin Sinha, BangDB

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Trino Software Foundation

Initial release

2012

1984

2016

2012

2020 rebranded from PrestoSQL

Current release

BangDB 2.0, October 2021

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Limited community edition free

commercial

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C, C++

C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
macOS

for devlopment

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

depending on connected data-source

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C#
C++
Java
Python

.Net
C#
Java
Perl
PHP
Python

C#
Java
PHP

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL

yes, depending on connected data-source

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

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

depending on connected data-source

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

depending on connected data-source

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

depending on connected data-source

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

depending on connected data-source

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)

fine grained access rights according to SQL-standard

yes

SQL standard access control

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
» more

Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

Trino is an open source project and usage is therefore free. Commercial offerings...
» more

News

One busy week to go before Trino Fest 2024
6 June 2024

60: Trino calling AI
22 May 2024

Big names round out the Trino Fest 2024 lineup
8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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