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DBMS > Google Cloud Bigtable

Google Cloud Bigtable System Properties

Please select another system to compare it with Google Cloud Bigtable.

Our visitors often compare Google Cloud Bigtable with Google Cloud Datastore, HBase and Amazon DynamoDB.

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Rank#134  Overall
#7  Wide column stores
Technical documentationcloud.google.com/­bigtable/­docs
Initial release2015
License infoCommercial or Open Sourcecommercial
Cloud-based infoOnly available as a cloud serviceyes
Server operating systemshosted
Data schemeschema-free
Typing infopredefined data types such as float or dateno
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.no
Secondary indexesno
SQL infoSupport of SQLno
APIs and other access methodsgRPC (using protocol buffers) API
HBase compatible API (Java)
Supported programming languagesGo
Server-side scripts infoStored proceduresno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Google Cloud Bigtable
Specific characteristics

Cloud Bigtable is a low latency, massively scalable wide-column NoSQL database for analytical and operational workloads (for example IoT, user analytics and financial analysis). As a fully managed Google Cloud Platform (GCP) offering, it benefits from industry leading security, availability and integration with other GCP capabilities. In addition to the original Bigtable API, Cloud Bigtable is fully compatible with an existing HBase™ setup, minimizing migration effort, and easing integration with other Apache™ capabilities such as Hadoop® and Spark™.

Check out the Cloud Bigtable Quickstarts for guidance on getting up and running.

Competitive advantages

Cloud Bigtable offers low latency and high throughput at any scale or application type, and can optimize your data over time for best performance. You can use Cloud Bigtable as the storage engine for large-scale, low-latency applications as well as throughput-intensive data processing and analytics.

Horizontally scalable with no downtime to match your data throughput needs

Fully Managed
Cloud Bigtable is offered as a fully managed service, meaning you spend your time developing valuable applications instead of configuring and tuning your database for performance and scalability. In addition, Google’s own Bigtable operations team monitors the service to ensure issues are addressed quickly.

Google Cloud Platform (GCP) integration allows easy creation of full solutions, and HBase API compatibility extends this into the open source Apache ecosystem Learn more...

Data security
Backups. Identity and access management. Learn more...

Typical application scenarios

Ad Tech / User Analytics
Integrate large volumes of unrefined data from many sources, typically to drive consistent customer activity across channels. Collect and compare large volumes of behavior data across customers to find common patterns that can drive recommendations and sales. Store which pages/videos/images/songs customers listened to, engaged in, how long they stayed, what they did while on the page, where they went next, and so on.

Build models based on historical behavior - continually update fraud patterns and compare with real-time transactions. Store and consolidate market data, trade activity, and other data, such as social and transactional data.

Ingest and analyze large volumes of time series data from sensors in real time - matching the high speeds the IoT data is generated to track normal and abnormal behavior. Enable customers to build dashboards and drive analytics on their data in real time.

Key customers

eBay, Spotify, Moloco, Pluribus Labs, Oden Technologies, Server Density, Google

Licensing and pricing models

When you use Cloud Bigtable, you are charged for the following:

  • The type of Cloud Bigtable instance, and the total number of nodes in your instance's clusters.
  • The amount of storage that your tables use.
  • The amount of network bandwidth that you use.

When you enable replication by creating an instance with 2 clusters, you are charged only for the items listed above, including the complete copy of the instance's data that is stored with the second cluster. There are no additional charges for replication beyond these standard items.

Pricing guide

3rd party products and services

We invite representatives of 3rd party vendors to contact us for presenting information about their offerings here.

More resources
Google Cloud Bigtable
Recent citations in the news

Google Cloud Platform adds more managed database services
25 April 2018, ZDNet

Google releases PostgreSQL support for Cloud SQL
26 April 2018, SDTimes.com

Google cloud database updates reinforce enterprise IT allure
27 April 2018, TechTarget

Google adds third cloud zone in Singapore
15 May 2018, ZDNet

How to Prevent the Friendly Cloud from Becoming a Foe Tomorrow?
15 May 2018, Data Center Knowledge

provided by Google News

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