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DBMS > Amazon Aurora vs. CrateDB vs. Google Cloud Firestore vs. Heroic

System Properties Comparison Amazon Aurora vs. CrateDB vs. Google Cloud Firestore vs. Heroic

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonDistributed Database based on LuceneCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Document storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websiteaws.amazon.com/­rds/­auroracratedb.comfirebase.google.com/­products/­firestoregithub.com/­spotify/­heroic
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcratedb.com/­docsfirebase.google.com/­docs/­firestorespotify.github.io/­heroic
DeveloperAmazonCrateGoogleSpotify
Initial release2015201320172014
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache 2.0
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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-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.yesnonono
Secondary indexesyesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
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
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)yes, Firebase Rules & Cloud Functionsno
Triggersyesnoyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyyesno
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.
More information provided by the system vendor
Amazon AuroraCrateDBGoogle Cloud FirestoreHeroic
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Amazon AuroraCrateDBGoogle Cloud FirestoreHeroic
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