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DBMS > Google Cloud Bigtable vs. Microsoft Azure Cosmos DB vs. SAP HANA vs. Vertica

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Cosmos DB vs. SAP HANA vs. Vertica

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSAP HANA  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Globally distributed, horizontally scalable, multi-model database serviceIn-memory, column based data store. Available as appliance or cloud serviceCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value store
Wide column store
Document store
Graph DBMS
Key-value store
Wide column store
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
Spatial DBMS
Time Series DBMS
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
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score44.27
Rank#23  Overall
#16  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­cosmos-dbwww.sap.com/­products/­hana.htmlwww.vertica.com
Technical documentationcloud.google.com/­bigtable/­docslearn.microsoft.com/­azure/­cosmos-dbhelp.sap.com/­hanavertica.com/­documentation
DeveloperGoogleMicrosoftSAPOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201420102005
Current release2.0 SPS07 (April 4, 2023), April 202312.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesyesno infoalso available as a cloud based serviceno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedAppliance or cloud-serviceLinux
Data schemeschema-freeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyes infoJSON typesyesyes
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 indexesnoyes infoAll properties auto-indexed by defaultyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
ODBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoJavaScriptSQLScript, Ryes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoJavaScriptyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud serviceyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyeswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*nono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsMulti-item ACID transactions with snapshot isolation within a partitionACIDACID
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Google Cloud BigtableMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSAP HANAVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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More resources
Google Cloud BigtableMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSAP HANAVertica infoOpenText™ Vertica™
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