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DBMS > Amazon Aurora vs. Apache Impala vs. Datastax Enterprise vs. Hazelcast

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Datastax Enterprise vs. Hazelcast

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.A widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSWide column storeKey-value store
Secondary database modelsDocument storeDocument storeDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoJSON support with IMDG 3.12
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
Score5.80
Rank#60  Overall
#4  Wide column stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.datastax.com/­products/­datastax-enterprisehazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.datastax.comhazelcast.org/­imdg/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDataStaxHazelcast
Initial release2015201320112008
Current release4.1.0, June 20226.8, April 20205.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemshostedLinuxLinux
OS X
All OS with a Java VM
Data schemeyesyesschema-freeschema-free
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.yesnonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JCache
JPA
Memcached protocol
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#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenoyes infoEvent Listeners, Executor Services
Triggersyesnoyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoAtomicity and isolation are supported for single operationsone or two-phase-commit; repeatable reads; read commited
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.yesnoyesyes
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 can be defined per objectRole-based access control
More information provided by the system vendor
Amazon AuroraApache ImpalaDatastax EnterpriseHazelcast
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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Amazon AuroraApache ImpalaDatastax EnterpriseHazelcast
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