TrustRadius: an HG Insights company

Google Cloud BigTable

Score9.5 out of 10

23 Reviews and Ratings

Get a Demo

What is Google Cloud BigTable?

Google's Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.

Categories & Use Cases

Key Features

Learn about the best (and worst!) features Google Cloud BigTable has to offer, as determined by TrustRadius' reviewers.
Based on 23 ratings of Google Cloud BigTable's features
View all features

Top Performing Features

  • Automatic software patching

    Patches applied to database automatically

    Category average: 8.3

  • Automatic host deployment

    Compute instance replacement in the event of hardware failure

    Category average: 6.8

  • Database scalability

    Ease of scaling compute or memory resources and storage up or down

    Category average: 9.2

Areas for Improvement

  • Automated backups

    Automated backup enabling point-in-time data recovery

    Category average: 8

  • Database security provisions

    Provision for database encryption, network isolation, and identity access management

    Category average: 8.8

  • Monitoring and metrics

    Built-in monitoring of multiple operational metrics

    Category average: 6.8

Reviews

What users are saying about Google Cloud BigTable.
View all reviews

Google Cloud BigTable gives you speed

Incentivized
Verified User
C-Level Executive in Engineering (201-500 employees employees)

Use Cases and Deployment Scope

We use Google Cloud BigTable to help us do the following:

1. Store aggregates

2. Build and keep lookup tables

3. Have a storage that can be looked up really fast to find duplicates

4. Given the large no. of txns it can handle, we use it for enriching our data from pipelines thus having rich information in the flows below.

Pros

  • High throughput
  • Low latency
  • Uptime
  • Fast Key-value lookups

Cons

  • Global replication
  • Complete SQL support
  • Size limit of 1MB

Return on Investment

  • Building new features that can leverage storage on the edge
  • Realtime decision making
  • Data enrichment

Usability

Alternatives Considered

Amazon DynamoDB and Apache CouchDB

Other Software Used

Google BigQuery, Cloudflare, Google Cloud CDN

Unlock the potential of your BigData with Google's BigTable!

Incentivized
Verified User
Advisor in Information Technology (10,001+ employees employees)

Use Cases and Deployment Scope

Analytics for big data is our biggest use case for Google Cloud's BigTable platform. It is efficient enough to read, handle and analyse TBs of data under unbelievable times.

Majorly, we have a lot of data captured from customer interactions with our applications which is required to be processed and analysed for gaining benefits from those data sets. Now, this data is so huge as it is accumulated every minute from each applications. Our traditional systems cannot process them all that once, and even if we can do slotting and then anaylse them, it will take longer durations and with that new data is ready to be consumed. So as to solve this problem, we started working on BigTable which has huge capabilities and Google's analytical skills. Its efficient and most importantly - fast!

Pros

  • Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
  • Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
  • Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.

Cons

  • User interface's responsiveness: I understand so much is going on under the hood, but laggyness is acceptable if a workload is running or being processed. In case their is not workload being process, GUI should work blazing fast. I have faced this at times, and this becomes frustrating as well.
  • Nothing other than this - BigTable is quite efficient platform and does exactly what it is built for.

Return on Investment

  • Positive return on investment.

Other Software Used

Google AdSense, Google Cloud Anthos Service Mesh, Google Cloud Dataflow, Google Cloud Datastore

Usability