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DBMS > Google Cloud Bigtable vs. HyperSQL vs. Informix vs. Microsoft Azure Table Storage

System Properties Comparison Google Cloud Bigtable vs. HyperSQL vs. Informix vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonInformix  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.Multithreaded, transactional RDBMS written in Java infoalso known as HSQLDBA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBWide column store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitecloud.google.com/­bigtablehsqldb.orgwww.ibm.com/­products/­informixazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­bigtable/­docshsqldb.org/­web/­hsqlDocsFrame.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
DeveloperGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Microsoft
Initial release2015200119842012
Current release2.7.2, June 202314.10.FC5, November 2020
License infoCommercial or Open SourcecommercialOpen Source infobased on BSD licensecommercial 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, C++ and Java
Server operating systemshostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesAIX
HP-UX
Linux
macOS
Solaris
Windows
hosted
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API infoJDBC via HTTP
JDBC
ODBC
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC
Java
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoJava, SQLyesno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding 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 zonesnoneMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDoptimistic locking
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authentication, authorization, and auditing controlsAccess rights based on private key authentication or shared access signatures

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More resources
Google Cloud BigtableHyperSQL infoalso known as HSQLDBInformixMicrosoft Azure Table Storage
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