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DBMS > GeoMesa vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. Riak KV

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. Riak KV

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Distributed, fault tolerant key-value store
Primary database modelSpatial DBMSKey-value store
Wide column store
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitewww.geomesa.orgcloud.google.com/­bigtablecloud.google.com/­spanner
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperCCRi and othersGoogleGoogleOpenSource, formerly Basho Technologies
Initial release2014201520172009
Current release5.0.0, May 20243.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaErlang
Server operating systemshostedhostedLinux
OS X
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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 indexesyesnoyesrestricted
SQL infoSupport of SQLnonoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnononoErlang
Triggersnononoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID infoStrict serializable isolationno
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.depending on storage layernono
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Security

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More resources
GeoMesaGoogle Cloud BigtableGoogle Cloud SpannerRiak KV
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