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DBMS > Amazon SimpleDB vs. Apache Impala vs. Drizzle vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Drizzle vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonTimescaleDB  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.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#139  Overall
#24  Key-value stores
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­simpledbimpala.apache.orgwww.timescale.com
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmldocs.timescale.com
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerTimescale
Initial release2007201320082017
Current release4.1.0, June 20227.2.4, September 20122.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyes
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infowith proprietary extensionsyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonono infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBApache ImpalaDrizzleTimescaleDB
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Recent citations in the news

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