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DBMS > Amazon Aurora vs. Apache Impala vs. Drizzle vs. DuckDB

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Drizzle vs. DuckDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonDuckDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.An embeddable, in-process, column-oriented SQL OLAP RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgduckdb.org
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlduckdb.org/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian Aker
Initial release2015201320082018
Current release4.1.0, June 20227.2.4, September 20120.10, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++
Server operating systemshostedLinuxFreeBSD
Linux
OS X
server-less
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infowith proprietary extensionsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBCArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBCC
C++
Java
PHP
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenono
Triggersyesnono infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPno

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More resources
Amazon AuroraApache ImpalaDrizzleDuckDB
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Recent citations in the news

Baffle enables computation on encrypted Amazon RDS and Aurora data – Blocks and Files
1 May 2024, Blocks and Files

Baffle Delivers Enterprise-Grade Data Security for PostgreSQL on Amazon RDS and Amazon Aurora
1 May 2024, Yahoo Finance

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ...
18 April 2024, AWS Blog

New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ...
8 November 2023, AWS Blog

provided by Google News

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

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

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB and AWS — How to Aggregate 100 Million Rows in 1 Minute
18 April 2024, Towards Data Science

Seattle startup MotherDuck raises $52.5M at a $400M valuation to fuel DuckDB analytics platform
20 September 2023, GeekWire

provided by Google News



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