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DBMS > Amazon Aurora vs. Google Cloud Bigtable vs. Hazelcast vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Google Cloud Bigtable vs. Hazelcast vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeRelational DBMS
Secondary database modelsDocument storeDocument 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­auroracloud.google.com/­bigtablehazelcast.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGoogleHazelcastApache Software Foundation
Initial release2015201520082014
Current release5.3.6, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemshostedhostedAll OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
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
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes infoEvent Listeners, Executor Servicesno
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)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 dataACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedno
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.yesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlno

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More resources
Amazon AuroraGoogle Cloud BigtableHazelcastSpark SQL
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