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DBMS > Google BigQuery vs. Google Cloud Datastore vs. Hypertable vs. Oracle Berkeley DB vs. Snowflake

System Properties Comparison Google BigQuery vs. Google Cloud Datastore vs. Hypertable vs. Oracle Berkeley DB vs. Snowflake

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSnowflake  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service with append-only tablesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopWidely used in-process key-value storeCloud-based data warehousing service for structured and semi-structured data
Primary database modelRelational DBMSDocument storeWide column storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score130.36
Rank#8  Overall
#5  Relational DBMS
Websitecloud.google.com/­bigquerycloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.snowflake.com
Technical documentationcloud.google.com/­bigquery/­docscloud.google.com/­datastore/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmldocs.snowflake.net/­manuals/­index.html
DeveloperGoogleGoogleHypertable Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleSnowflake Computing Inc.
Initial release20102008200919942014
Current release0.9.8.11, March 201618.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
hosted
Data schemeyesschema-freeschema-freeschema-freeyes infosupport of semi-structured data formats (JSON, XML, Avro)
Typing infopredefined data types such as float or dateyesyes, details herenonoyes
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.nonoyes infoonly with the Berkeley DB XML editionyes
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
CLI Client
JDBC
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptusing Google App Enginenonouser defined functions
TriggersnoCallbacks using the Google Apps Enginenoyes infoonly for the SQL APIno infosimilar concept for controling cloud resources
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor on file system levelSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 datano infoSince BigQuery is designed for querying dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoUsers with fine-grained authorization concept, user roles and pluggable authentication

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More resources
Google BigQueryGoogle Cloud DatastoreHypertableOracle Berkeley DBSnowflake
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