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DBMS > BoltDB vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb

System Properties Comparison BoltDB vs. Google Cloud Datastore vs. Manticore Search vs. Microsoft Azure Table Storage vs. Oracle Rdb

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Rdb  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value storeDocument storeSearch engineWide column storeRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.14
Rank#178  Overall
#80  Relational DBMS
Websitegithub.com/­boltdb/­boltcloud.google.com/­datastoremanticoresearch.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationcloud.google.com/­datastore/­docsmanual.manticoresearch.comwww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperGoogleManticore SoftwareMicrosoftOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release20132008201720121984
Current release6.0, February 20237.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoGPL version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedFreeBSD
Linux
macOS
Windows
hostedHP Open VMS
Data schemeschema-freeschema-freeFixed schemaschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or datenoyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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.nonoCan index from XMLnono
Secondary indexesnoyesyes infofull-text index on all search fieldsnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languagenoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsno
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSynchronous replication based on Galera libraryyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesoptimistic lockingyes, on a single node
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signatures

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More resources
BoltDBGoogle Cloud DatastoreManticore SearchMicrosoft Azure Table StorageOracle Rdb
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