DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google BigQuery vs. InfinityDB vs. Microsoft Azure Table Storage vs. SAP HANA

System Properties Comparison Google BigQuery vs. InfinityDB vs. Microsoft Azure Table Storage vs. SAP HANA

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA Java embedded Key-Value Store which extends the Java Map interfaceA Wide Column Store for rapid development using massive semi-structured datasetsIn-memory, column based data store. Available as appliance or cloud service
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score0.07
Rank#359  Overall
#54  Key-value stores
Score4.92
Rank#73  Overall
#6  Wide column stores
Score45.84
Rank#22  Overall
#16  Relational DBMS
Websitecloud.google.com/­bigqueryboilerbay.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.sap.com/­products/­hana.html
Technical documentationcloud.google.com/­bigquery/­docsboilerbay.com/­infinitydb/­manualhelp.sap.com/­hana
DeveloperGoogleBoiler Bay Inc.MicrosoftSAP
Initial release2010200220122010
Current release4.02.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VMhostedAppliance or cloud-service
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nononono
Secondary indexesnono infomanual creation possible, using inversions based on multi-value capabilitynoyes
SQL infoSupport of SQLyesnonoyes
APIs and other access methodsRESTful HTTP/JSON APIAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
RESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Java.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnonoSQLScript, R
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infoOptimistic locking for transactions; no isolation for bulk loadsoptimistic lockingACID
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.nononoyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesyes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more
CData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google BigQueryInfinityDBMicrosoft Azure Table StorageSAP HANA
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2022, defending the title from last year
3 January 2023, Matthias Gelbmann, Paul Andlinger

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

Winning the 2020 Google Cloud Technology Partner of the Year – Infrastructure Modernization Award
22 December 2021, CIO

Google’s Logica language addresses SQL’s flaws
15 April 2021, InfoWorld

Google Cloud Platform breaks through with big enterprises, signs up Disney and others
23 March 2016, ZDNet

Benefits of a Hybrid Data Lake. How to combine a Data Warehouse with a… | by Christianlauer
14 January 2021, Towards Data Science

Hightouch Raises $38M in Funding
19 July 2023, FinSMEs

provided by Google News

Azure Cosmos DB Data Migration tool imports from Azure Table storage | Azure updates
5 May 2015, azure.microsoft.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Testing Precompiled Azure Functions Locally with Storage Emulator
8 March 2018, Visual Studio Magazine

provided by Google News

Combine the Power of AI with Business Context Using SAP HANA Cloud Vector Engine
2 April 2024, SAP News

Automating application-consistent Amazon EBS Snapshots for SAP HANA databases | Amazon Web Services
6 February 2024, AWS Blog

Modernize consolidation in an SAP S/4 HANA environment | CCH Tagetik
9 April 2024, Wolters Kluwer

SAP HANA Cloud Vector Engine
18 April 2024, IgniteSAP

What are the options as SAP HANA 1.0 support in the Neo environment sunsets?
3 November 2023, ComputerWeekly.com

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here