DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google BigQuery vs. InterSystems Caché vs. SAP HANA vs. Vitess

System Properties Comparison Google BigQuery vs. InterSystems Caché vs. SAP HANA vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSAP HANA  Xexclude from comparisonVitess  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionLarge scale data warehouse service with append-only tablesA multi-model DBMS and application serverIn-memory, column based data store. Available as appliance or cloud serviceScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score44.27
Rank#23  Overall
#16  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitecloud.google.com/­bigquerywww.intersystems.com/­products/­cachewww.sap.com/­products/­hana.htmlvitess.io
Technical documentationcloud.google.com/­bigquery/­docsdocs.intersystems.comhelp.sap.com/­hanavitess.io/­docs
DeveloperGoogleInterSystemsSAPThe Linux Foundation, PlanetScale
Initial release2010199720102013
Current release2018.1.4, May 20202.0 SPS07 (April 4, 2023), April 202315.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono infoalso available as a cloud based serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Appliance or cloud-serviceDocker
Linux
macOS
Data schemeyesdepending on used data modelyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesyesyesyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP/JSON API.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Java
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyesSQLScript, Ryes infoproprietary syntax
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noyesyesyes
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 rolesyesUsers with fine-grained authorization concept infono user groups or roles

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 BigQueryInterSystems CachéSAP HANAVitess
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 Cloud partners Coinbase to accept crypto payments
11 October 2022, Ledger Insights

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

provided by Google News

AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner
12 February 2022, CRN

Epic On EHR Interoperability: Not A '1-Time Project'
10 April 2015, InformationWeek

Associative Data Modeling Demystified - Part1 - DataScienceCentral.com
9 July 2016, Data Science Central

Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future
24 June 2022, IBM

Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi
23 February 2020, Towards Data Science

provided by Google News

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

SAP customers may struggle to escape ECC before support shutters if they don't start now
12 June 2024, The Register

Accenture and SAP Accelerate Business Transformation with AI
14 June 2024, InsideSAP

5 New Google Cloud-SAP Products Launched At Sapphire For AI, HANA And Cloud
4 June 2024, CRN

Automating the update process of a clustered SAP HANA DB using nZDT and Ansible | Amazon Web Services
16 November 2023, AWS Blog

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

provided by Google News



Share this page

Featured Products

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

Milvus logo

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

Neo4j logo

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

Present your product here