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DBMS > Amazon Aurora vs. Databend vs. Google Cloud Bigtable vs. Hazelcast

System Properties Comparison Amazon Aurora vs. Databend vs. Google Cloud Bigtable vs. Hazelcast

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabend  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityGoogle'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 grid
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.84
Rank#44  Overall
#28  Relational DBMS
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­auroragithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­bigtablehazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databend.comcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docs
DeveloperAmazonDatabend LabsGoogleHazelcast
Initial release2015202120152008
Current release1.0.59, April 20235.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava
Server operating systemshostedhosted
Linux
macOS
hostedAll OS with a Java VM
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesnonoyes
SQL infoSupport of SQLyesyesnoSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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
Go
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesnonoyes infoEvent Listeners, Executor Services
Triggersyesnonoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingSharding
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 Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 dataACIDyesAtomic single-row 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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Amazon AuroraDatabendGoogle Cloud BigtableHazelcast
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