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DBMS > Amazon Aurora vs. BigObject vs. Google Cloud Bigtable vs. Hazelcast vs. OrigoDB

System Properties Comparison Amazon Aurora vs. BigObject vs. Google Cloud Bigtable vs. Hazelcast vs. OrigoDB

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonOrigoDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for real-time computations and queriesGoogle'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 gridA fully ACID in-memory object graph database
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Wide column store
Key-value storeDocument store
Object oriented 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Websiteaws.amazon.com/­rds/­aurorabigobject.iocloud.google.com/­bigtablehazelcast.comorigodb.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.bigobject.iocloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsorigodb.com/­docs
DeveloperAmazonBigObject, Inc.GoogleHazelcastRobert Friberg et al
Initial release20152015201520082009 infounder the name LiveDB
Current release5.3.6, November 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedAll OS with a Java VMLinux
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyesUser defined using .NET types and collections
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 strategyno infocan be achieved using .NET
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL-like query languageno
APIs and other access methodsADO.NET
JDBC
ODBC
fluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
HTTP API
LINQ
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
.Net
Server-side scripts infoStored proceduresyesLuanoyes infoEvent Listeners, Executor Servicesyes
Triggersyesnonoyes infoEventsyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate 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 integrityyesyes infoautomatically between fact table and dimension tablesnonodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlRole based authorization

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More resources
Amazon AuroraBigObjectGoogle Cloud BigtableHazelcastOrigoDB
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