DBMS > Apache Impala vs. Badger vs. Bangdb vs. Microsoft Azure Synapse Analytics vs. Trino

System Properties Comparison Apache Impala vs. Badger vs. Bangdb vs. Microsoft Azure Synapse Analytics vs. Trino

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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

Relational DBMS

Key-value store

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store

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	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

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	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

impala.apache.org

github.com/dgraph-io/badger

bangdb.com

azure.microsoft.com/services/synapse-analytics

trino.io

Technical documentation

impala.apache.org/impala-docs.html

godoc.org/github.com/dgraph-io/badger

docs.bangdb.com

docs.microsoft.com/azure/synapse-analytics

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

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DGraph Labs

Sachin Sinha, BangDB

Microsoft

Trino Software Foundation

Initial release

2013

2017

2012

2016

2012

2020 rebranded from PrestoSQL

Current release

4.1.0, June 2022

BangDB 2.0, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

BSD 3

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++

C++

Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Linux
macOS

for devlopment

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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 DML and DDL statements

SQL like support with command line tool

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

C#
Java
PHP

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

yes, depending on connected data-source

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding, horizontal partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Tunable consistency, set CAP knob accordingly

Immediate Consistency

depending on connected data-source

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

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes (enterprise version only)

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

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

Time travel in Delta Lake connector
11 April 2024

58: Understanding your users with Trino and Mitzu
4 April 2024

57: Seeing clearly with OpenTelemetry
14 March 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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