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DBMS > Amazon SimpleDB vs. GeoSpock vs. Google Cloud Bigtable vs. HBase vs. Lovefield

System Properties Comparison Amazon SimpleDB vs. GeoSpock vs. Google Cloud Bigtable vs. HBase vs. Lovefield

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonLovefield  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreSpatial and temporal data processing engine for extreme data scaleGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableEmbeddable relational database for web apps written in pure JavaScript
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Wide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Websiteaws.amazon.com/­simpledbgeospock.comcloud.google.com/­bigtablehbase.apache.orggoogle.github.io/­lovefield
Technical documentationdocs.aws.amazon.com/­simpledbcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperAmazonGeoSpockGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetGoogle
Initial release2007201520082014
Current release2.0, September 20192.3.4, January 20212.1.12, February 2017
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptJavaJavaScript
Server operating systemshostedhostedhostedLinux
Unix
Windows infousing Cygwin
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenoyesnooptions to bring your own types, AVROyes
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.nononono
Secondary indexesyes infoAll columns are indexed automaticallytemporal, categoricalnonoyes
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)nonoSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
JavaScript
Server-side scripts infoStored proceduresnononoyes infoCoprocessors in Javano
TriggersnononoyesUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationAutomatic shardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoAtomic single-row operationsSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infousing MemoryDB
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
Amazon SimpleDBGeoSpockGoogle Cloud BigtableHBaseLovefield
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