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 Cloud Spanner vs. IBM Db2 warehouse vs. Kinetica vs. Microsoft Azure Table Storage

System Properties Comparison Google Cloud Spanner vs. IBM Db2 warehouse vs. Kinetica vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Cloud-based data warehousing serviceFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitecloud.google.com/­spannerwww.ibm.com/­products/­db2/­warehousewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­spanner/­docsdocs.kinetica.com
DeveloperGoogleIBMKineticaMicrosoft
Initial release2017201420122012
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemshostedhostedLinuxhosted
Data schemeyesyesyesschema-free
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.nono infoImport/export of XML data possiblenono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yesSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoPL/SQL, SQL PLuser defined functionsno
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
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 nodesMulti-source replication with 3 replicas for regional instances.yesSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDnooptimistic 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.noyesyes infoGPU vRAM or System RAMno
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-standardAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures

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

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

More resources
Google Cloud SpannerIBM Db2 warehouse infoformerly named IBM dashDBKineticaMicrosoft Azure Table Storage
Recent citations in the news

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Cloud Spanner Is Now Half the Cost of Amazon DynamoDB
13 October 2023, Datanami

Google Spanner: When Do You Need to Move to It?
11 September 2023, hackernoon.com

Google Cloud Spanner competes directly with Amazon DynamoDB
12 October 2023, Techzine Europe

provided by Google News

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ...
11 July 2023, IBM

Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x
11 July 2023, IBM

The 10 Best Cloud Data Warehouse Solutions to Consider in 2024
22 October 2023, Solutions Review

Data mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

Announcing the availability of Bring-Your-Own-License and Reserved Instance plans for next generation Db2 ...
7 August 2023, IBM

provided by Google News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

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

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

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

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