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DBMS > Amazon Aurora vs. Apache Impala vs. Google Cloud Bigtable vs. TerarkDB vs. TimesTen

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Google Cloud Bigtable vs. TerarkDB vs. TimesTen

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTerarkDB  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value storeRelational 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcloud.google.com/­bigtablegithub.com/­bytedance/­terarkdbwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.oracle.com/­database/­timesten-18.1
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleByteDance, originally TerarkOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20152013201520161998
Current release4.1.0, June 202211 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial inforestricted open source version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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.yesnononono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnonoyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
C++ API
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
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++
Go
Java
JavaScript (Node.js)
Python
C++
Java
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenonoPL/SQL
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache ImpalaGoogle Cloud BigtableTerarkDBTimesTen
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