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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google BigQuery

    Score8.8 out of 10
    N/AGoogle's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

    $6.25

    per TiB (after the 1st 1 TiB per month, which is free)

    Twilio Segment

    Score8.4 out of 10
    N/ASegment is a customer data platform that helps engineering teams at companies like Tradesy, TIME, Inc., Gap, Lending Tree, PayPal, and Fender, etc., achieve time and cost savings on their data infrastructure, which was acquired by Twilio November 2020. The vendor says they also enable Product, BI, and Marketing teams to access 200+ tools (Mixpanel, Salesforce, Marketo, Redshift, etc.) to better understand and optimize customer preferences for growth— all integrations are pre-built and…

    $120

    per month

    Pricing
    Google BigQueryTwilio Segment
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Free
    $0.00
    Includes 1,000 visitors/mo
    Team
    $120.00
    Includes 10,000 visitors/mo
    Business
    Contact Sales
    Custom Volume
    Offerings
    Pricing Offerings
    Google BigQueryTwilio Segment
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryTwilio Segment
    Considered Both Products
    Google
    No answer on this topic
    Twilio
    Chose Twilio Segment
    Segment is considerably cheaper but doesn't have the GUI for non-SQL users. GA Premium doesn't have all the data connectors, and can be more difficult to configure on SPAs.
    Incentivized
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    100%
    Would buy again
    14 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    100%
    Happy with the feature set
    14 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    100%
    Lived up to sales and marketing promises
    12 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    86%
    Implementation went as expected
    12 Answers
    Features
    Google BigQueryTwilio Segment
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Twilio Segment
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Twilio Segment
    -
    Ratings
    Automatic software patching8.017 Ratings00 Ratings
    Database scalability9.079 Ratings00 Ratings
    Automated backups8.524 Ratings00 Ratings
    Database security provisions8.873 Ratings00 Ratings
    Monitoring and metrics8.675 Ratings00 Ratings
    Automatic host deployment8.013 Ratings00 Ratings
    Tag Management
    Comparison of Tag Management features of Google BigQuery and Twilio Segment
    Feature
    Google BigQuery
    -
    Ratings
    Twilio Segment
    7.6
    2 Ratings
    8% below category average
    Tag library00 Ratings8.01 Ratings
    Tag variable mapping00 Ratings8.01 Ratings
    Ease of writing custom tags00 Ratings8.01 Ratings
    Rules-driven tag execution00 Ratings7.01 Ratings
    Tag performance monitoring00 Ratings7.01 Ratings
    Page load times00 Ratings8.01 Ratings
    Mobile app tagging00 Ratings7.01 Ratings
    Library of JavaScript extensions00 Ratings7.52 Ratings
    Audience Segmentation & Targeting
    Comparison of Audience Segmentation & Targeting features of Google BigQuery and Twilio Segment
    Feature
    Google BigQuery
    -
    Ratings
    Twilio Segment
    7.6
    2 Ratings
    7% below category average
    Standard visitor segmentation00 Ratings8.02 Ratings
    Behavioral visitor segmentation00 Ratings7.52 Ratings
    Traffic allocation control00 Ratings7.02 Ratings
    Website personalization00 Ratings8.01 Ratings
    Customer Data Management
    Comparison of Customer Data Management features of Google BigQuery and Twilio Segment
    Feature
    Google BigQuery
    -
    Ratings
    Twilio Segment
    8.3
    3 Ratings
    2% above category average
    Account Scoring00 Ratings8.52 Ratings
    Customer Data Governance00 Ratings9.02 Ratings
    Data Connectors00 Ratings8.73 Ratings
    Data Enhancement00 Ratings8.02 Ratings
    Data Ingestion00 Ratings8.73 Ratings
    Data Storage00 Ratings8.52 Ratings
    Data Visibility00 Ratings8.02 Ratings
    Event Data00 Ratings8.02 Ratings
    Identity Resolution00 Ratings7.52 Ratings
    Best Alternatives
    Google BigQueryTwilio Segment
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    No answers on this topic
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    Treasure AI
    Score9 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    Treasure AI
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryTwilio Segment
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.7
    (21 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    -
    (0 ratings)
    Usability
    6.6
    (6 ratings)
    -
    (0 ratings)
    Availability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.4
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    4.8
    (11 ratings)
    7.7
    (8 ratings)
    Configurability
    6.4
    (1 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    7.3
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Google BigQueryTwilio Segment
    Likelihood to Recommend
    Google
    Event-based data can be captured seamlessly from our data layers (and exported to Google BigQuery). When events like page-views, clicks, add-to-cart are tracked, Google BigQuery can help efficiently with running queries to observe patterns in user behaviour. That intermediate step of trying to "untangle" event data is resolved by Google BigQuery. A scenario where it could possibly be less appropriate is when analysing "granular" details (like small changes to a database happening very frequently).
    Incentivized
    Read full review
    Twilio
    Best suited: - Merging emails coming from: Facebook leads forms, Unbounce or landing pages forms, Google forms, any other kind of lead generation tool and bundling all that information together for a single user "profile". - Passing events generated in multiple applications by the same user (product selected in web, product discarded in cart, etc) and delivering those events into other applications (like a CRM) Less appropriate: - Reading/updating data directly from segment from a frontend application
    Incentivized
    Read full review
    Pros
    Google
    • Realtime integration with Google Sheets.
    • GSheet data can be linked to a BigQuery table and the data in that sheet is ingested in realtime into BigQuery. It's a live 'sync' which means it supports insertions, deletions, and alterations. The only limitation here is the schema'; this remains static once the table is created.
    • Seamless integration with other GCP products.
    • A simple pipeline might look like this:-
    • GForms -> GSheets -> BigQuery -> Looker
    • It all links up really well and with ease.
    • One instance holds many projects.
    • Separating data into datamarts or datameshes is really easy in BigQuery, since one BigQuery instance can hold multiple projects; which are isolated collections of datasets.
    Incentivized
    Read full review
    Twilio
    • Multi-platform. Segment has easy integrations in many different web, backend, and app platforms/frameworks. We use the Segment SDK in Android and iOS as well as our node.js backend.
    • Segment is fairly affordable for early-stage companies that are trying out different analytics software. The "developer" plan is free and is suitable for most companies with products that have a small user base.
    • The UI is great! It is extremely intuitive and easy-to-learn, and this made it take very little time to integrate this software into our analytics and marketing workflows.
    Incentivized
    Read full review
    Cons
    Google
    • Please expand the availability of documentation, tutorials, and community forums to provide developers with comprehensive support and guidance on using Google BigQuery effectively for their projects.
    • If possible, simplify the pricing model and provide clearer cost breakdowns to help users understand and plan for expenses when using Google BigQuery. Also, some cost reduction is welcome.
    • It still misses the process of importing data into Google BigQuery. Probably, by improving compatibility with different data formats and sources and reducing the complexity of data ingestion workflows, it can be made to work.
    Incentivized
    Read full review
    Twilio
    • More and richer sources. For example, MailChimp is a source but the data you get from MailChimp is quite limited. I ended up writing my own scripts to take better advantage of MailChimp's API because Segment's integration was lacking.
    • Better examples on how to set up event tracking. Pageview tracking is easy enough, but it would be nice if they had a sample app and corresponding code for it and showed you, via Git commits, how to add various kinds of events.
    Incentivized
    Read full review
    Likelihood to Renew
    Google
    We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
    Incentivized
    Read full review
    Twilio
    No answers on this topic
    Usability
    Google
    I think overall it is easy to use. I haven't done anything from the development side but an more of an end user of reporting tables built in Google BigQuery. I connect data visualization tools like Tableau or Power BI to the BigQuery reporting tables to analyze trends and create complex dashboards.
    Incentivized
    Read full review
    Twilio
    No answers on this topic
    Reliability and Availability
    Google
    I have never had any significant issues with Google Big Query. It always seems to be up and running properly when I need it. I cannot recall any times where I received any kind of application errors or unplanned outages. If there were any they were resolved quickly by my IT team so I didn't notice them.
    Incentivized
    Read full review
    Twilio
    No answers on this topic
    Performance
    Google
    I think Google Big Query's performance is in the acceptable range. Sometimes larger datasets are somewhat sluggish to load but for most of our applications it performs at a reasonable speed. We do have some reports that include a lot of complex calculations and others that run on granular store level data that so sometimes take a bit longer to load which can be frustrating.
    Incentivized
    Read full review
    Twilio
    No answers on this topic
    Support Rating
    Google
    BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
    Incentivized
    Read full review
    Twilio
    Over the period it took us to set up, we kept going back to their enablement team to help us with the setup, and they were always ready and were very helpful in the entire process. Even with their documentation, they took the time out to help us work through the process. We've never had a message/email unanswered for more than an hour on working days.
    Incentivized
    Read full review
    Alternatives Considered
    Google
    PowerBI can connect to GA4 for example but the data processing is more complicated and it takes longer to create dashboards. Azure is great once the data import has been configured but it's not an easy task for small businesses as it is with BigQuery.
    Incentivized
    Read full review
    Twilio
    We chose Twilio Segment for the good API integration and node resources, I would use Ontraport again, particularly if I didn't have the requirements for API and development/platform integration. Certainly the set up and management is easy and seamless with both the API and the user interface to use depending on circumstances and requirements.
    Incentivized
    Read full review
    Contract Terms and Pricing Model
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Twilio
    No answers on this topic
    Scalability
    Google
    We have continued to expand out use of Google Big Query over the years. I'd say its flexibility and scalability is actually quite good. It also integrates well with other tools like Tableau and Power BI. It has served the needs of multiple data sources across multiple departments within my company.
    Incentivized
    Read full review
    Twilio
    No answers on this topic
    Professional Services
    Google
    Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
    Read full review
    Twilio
    No answers on this topic
    Return on Investment
    Google
    • Previously, running complex queries on our on-premise data warehouse could take hours. Google BigQuery processes the same queries in minutes. We estimate it saves our team at least 25% of their time.
    • We can target our marketing campaigns very easily and understand our customer behaviour. It lets us personalize marketing campaigns and product recommendations and experience at least a 20% improvement in overall campaign performance.
    • Now, we only pay for the resources we use. Saved $1 million annually on data infrastructure and data storage costs compared to our previous solution.
    Incentivized
    Read full review
    Twilio
    • Segment has enabled us to get a full view of our front end activity, join it to our back-end activity, and get full visibility into our funnels and user activity.
    • Segment lets us send events to ad tools with a full audit trail so all the numbers line up.
    • Segment also brings data from other sources into our data warehouse, saving our data engineering time from building commodity connectors.
    Read full review
    ScreenShots

    Google BigQuery Screenshots

    Screenshot of Migrating data warehouses to BigQuery - Features a streamlined migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the fully managed BigQuery Migration Service.Screenshot of bringing any data into BigQuery - Data files can be uploaded from local sources, Google Drive, or Cloud Storage buckets, using BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, by replicating data from relational databases with Datastream for BigQuery, or by leveraging Google's data integration partnerships.Screenshot of generative AI use cases with BigQuery and Gemini models - Data pipelines that blend structured data, unstructured data and generative AI models together can be built to create a new class of analytical applications. BigQuery integrates with Gemini 1.0 Pro using Vertex AI. The Gemini 1.0 Pro model is designed for higher input/output scale and better result quality across a wide range of tasks like text summarization and sentiment analysis. It can be accessed using simple SQL statements or BigQuery’s embedded DataFrame API from right inside the BigQuery console.Screenshot of insights derived from images, documents, and audio files, combined with structured data - Unstructured data represents a large portion of untapped enterprise data. However, it can be challenging to interpret, making it difficult to extract meaningful insights from it. Leveraging the power of BigLake, users can derive insights from images, documents, and audio files using a broad range of AI models including Vertex AI’s vision, document processing, and speech-to-text APIs, open-source TensorFlow Hub models, or custom models.Screenshot of event-driven analysis - Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows users to make business decisions based on the freshest data. Or Dataflow can be used to enable simplified streaming data pipelines.Screenshot of predicting business outcomes AI/ML - Predictive analytics can be used to streamline operations, boost revenue, and mitigate risk. BigQuery ML democratizes the use of ML by empowering data analysts to build and run models using existing business intelligence tools and spreadsheets.

    Twilio Segment Screenshots

    Screenshot of Destinations CatalogScreenshot of Destinations Main OverviewScreenshot of Sources Main OverviewScreenshot of DebuggerScreenshot of DocsScreenshot of Destination Settings