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DBMS > Apache Impala vs. Faircom DB vs. Trino

System Properties Comparison Apache Impala vs. Faircom DB vs. Trino

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score5.00
Rank#66  Overall
#36  Relational DBMS
Websiteimpala.apache.orgwww.faircom.com/­products/­faircom-dbtrino.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmltrino.io/­broadcast
trino.io/­docs/­current
Social network pagesLinkedInTwitterYouTubeGitHub
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationTrino Software Foundation
Initial release201319792012 info2020 rebranded from PrestoSQL
Current release4.1.0, June 2022V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoRestricted, free version availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase 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 languageC++ANSI C, C++Java
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS infofor devlopment
Data schemeyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesdepending on connected data-source
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++yes, depending on connected data-source
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).depending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on connected data-source
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memorydepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesSQL standard access control
More information provided by the system vendor
Apache ImpalaFaircom DB infoformerly c-treeACETrino
Specific characteristicsTrino is the fastest open source, massively parallel processing SQL query engine...
» more
Competitive advantagesHigh performance analtyics and data processing of very large data sets Powerful ANSI...
» more
Typical application scenariosPerformant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more
Key customersTrino is widely adopted across the globe as freely-available open source software....
» more
Market metrics33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more
Licensing and pricing modelsTrino is an open source project and usage is therefore free. Commercial offerings...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaFaircom DB infoformerly c-treeACETrino
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

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Starburst Brings Dataframes Into Trino Platform
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Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost | Amazon ...
4 October 2023, AWS Blog

Trino: The Open-source Data Query Engine That Split from Facebook
30 March 2022, hackernoon.com

A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

provided by Google News



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