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DBMS > Google Cloud Bigtable vs. Hive vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage

System Properties Comparison Google Cloud Bigtable vs. Hive vs. IBM Db2 Event Store vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value store
Wide column store
Relational DBMSEvent Store
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitecloud.google.com/­bigtablehive.apache.orgwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-store
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookIBMMicrosoft
Initial release2015201220172012
Current release3.1.3, April 20222.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++
Server operating systemshostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionhosted
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes
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.nonono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factorActive-active shard replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures

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More resources
Google Cloud BigtableHiveIBM Db2 Event StoreMicrosoft Azure Table Storage
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