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DBMS > Amazon Aurora vs. Apache Impala vs. Drizzle vs. EJDB vs. IBM Db2 Event Store

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Drizzle vs. EJDB vs. IBM Db2 Event Store

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonEJDB  Xexclude from comparisonIBM Db2 Event Store  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.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Distributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeEvent Store
Time Series 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
Score0.27
Rank#297  Overall
#44  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orggithub.com/­Softmotions/­ejdbwww.ibm.com/­products/­db2-event-store
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdwww.ibm.com/­docs/­en/­db2-event-store
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerSoftmotionsIBM
Initial release20152013200820122017
Current release4.1.0, June 20227.2.4, September 20122.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoGPLv2commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++CC and C++
Server operating systemshostedLinuxFreeBSD
Linux
OS X
server-lessLinux infoLinux, macOS, Windows for the developer addition
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infostring, integer, double, bool, date, object_idyes
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 indexesyesyesyesnono
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infowith proprietary extensionsnoyes infothrough the embedded Spark runtime
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBCin-process shared libraryADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
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
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenonoyes
Triggersyesnono infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
noneActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno infotypically not needed, however similar functionality with collection joins possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoRead/Write LockingNo - written data is immutable
Durability infoSupport for making data persistentyesyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
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, HTTPnofine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache ImpalaDrizzleEJDBIBM Db2 Event Store
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