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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)

    IBM Cognos Analytics

    Score7.7 out of 10
    N/AIBM Cognos is a full-featured business intelligence suite by IBM, designed for larger deployments. It comprises Query Studio, Reporting Studio, Analysis Studio and Event Studio, and Cognos Administration along with tools for Microsoft Office integration, full-text search, and dashboards.

    $11.25

    per month per user

    Pricing
    Google BigQueryIBM Cognos Analytics
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    On Demand - Standard
    USD 11.25
    per month per user
    On Demand - Premium
    USD 44.90
    per month per user
    Offerings
    Pricing Offerings
    Google BigQueryIBM Cognos Analytics
    Free Trial
    YesYes
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryIBM Cognos Analytics
    Considered Both Products
    Google
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    97%
    Would buy again
    92 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    94%
    Delivers good value for the price
    79 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    96%
    Happy with the feature set
    91 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    93%
    Lived up to sales and marketing promises
    55 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    96%
    Implementation went as expected
    64 Answers
    Features
    Google BigQueryIBM Cognos Analytics
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    IBM Cognos Analytics
    -
    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
    BI Standard Reporting
    Comparison of BI Standard Reporting features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    7.7
    138 Ratings
    6% below category average
    Pixel Perfect reports00 Ratings7.6129 Ratings
    Customizable dashboards00 Ratings8.0136 Ratings
    Report Formatting Templates00 Ratings7.5131 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    7.9
    138 Ratings
    1% below category average
    Drill-down analysis00 Ratings7.4136 Ratings
    Formatting capabilities00 Ratings8.3139 Ratings
    Integration with R or other statistical packages00 Ratings7.397 Ratings
    Report sharing and collaboration00 Ratings8.6133 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    9.2
    136 Ratings
    11% above category average
    Publish to Web00 Ratings9.836 Ratings
    Publish to PDF00 Ratings8.2132 Ratings
    Report Versioning00 Ratings9.833 Ratings
    Report Delivery Scheduling00 Ratings8.2134 Ratings
    Delivery to Remote Servers00 Ratings9.918 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    7.4
    124 Ratings
    8% below category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings7.9121 Ratings
    Location Analytics / Geographic Visualization00 Ratings8.0114 Ratings
    Predictive Analytics00 Ratings6.7110 Ratings
    Pattern Recognition and Data Mining00 Ratings6.947 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    7.8
    130 Ratings
    8% below category average
    Multi-User Support (named login)00 Ratings7.5129 Ratings
    Role-Based Security Model00 Ratings7.5127 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings7.4127 Ratings
    Report-Level Access Control00 Ratings8.257 Ratings
    Single Sign-On (SSO)00 Ratings8.6111 Ratings
    Mobile Capabilities
    Comparison of Mobile Capabilities features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    6.4
    109 Ratings
    19% below category average
    Responsive Design for Web Access00 Ratings6.8104 Ratings
    Mobile Application00 Ratings6.390 Ratings
    Dashboard / Report / Visualization Interactivity on Mobile00 Ratings6.696 Ratings
    Application Program Interfaces (APIs) / Embedding
    Comparison of Application Program Interfaces (APIs) / Embedding features of Google BigQuery and IBM Cognos Analytics
    Feature
    Google BigQuery
    -
    Ratings
    IBM Cognos Analytics
    9.2
    87 Ratings
    17% above category average
    REST API00 Ratings7.683 Ratings
    Javascript API00 Ratings7.779 Ratings
    iFrames00 Ratings9.912 Ratings
    Java API00 Ratings10.013 Ratings
    Themeable User Interface (UI)00 Ratings9.915 Ratings
    Customizable Platform (Open Source)00 Ratings9.99 Ratings
    Best Alternatives
    Google BigQueryIBM Cognos Analytics
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    Cyfe
    Score4 out of 10
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    Qlik Cloud Analytics (Qlik Sense)
    Score8.1 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    Jaspersoft Community Edition
    Score7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryIBM Cognos Analytics
    Likelihood to Recommend
    9.0
    (79 ratings)
    8.0
    (158 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    8.4
    (31 ratings)
    Usability
    6.6
    (6 ratings)
    7.3
    (10 ratings)
    Availability
    7.3
    (1 ratings)
    8.6
    (4 ratings)
    Performance
    6.4
    (1 ratings)
    9.0
    (5 ratings)
    Support Rating
    4.8
    (11 ratings)
    1.0
    (9 ratings)
    In-Person Training
    -
    (0 ratings)
    8.7
    (4 ratings)
    Online Training
    -
    (0 ratings)
    8.0
    (4 ratings)
    Implementation Rating
    -
    (0 ratings)
    7.0
    (7 ratings)
    Configurability
    6.4
    (1 ratings)
    7.0
    (3 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    -
    (0 ratings)
    8.6
    (40 ratings)
    Data Sources
    -
    (0 ratings)
    8.3
    (40 ratings)
    Ease of integration
    7.3
    (1 ratings)
    5.5
    (6 ratings)
    Product Scalability
    7.3
    (1 ratings)
    6.4
    (5 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    Vendor post-sale
    -
    (0 ratings)
    7.0
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    7.0
    (1 ratings)
    User Testimonials
    Google BigQueryIBM Cognos Analytics
    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
    IBM
    For Transaction monitoring, we build reports for executive management, providing insights into the number of alerts, the types or categories of detection scenarios, the risk profile, and a snapshot of high- or urgent-priority cases to be reported to AUSTRAC. Congos helps to build the report by ingesting alert data exported from SAS datasets. It joins with other data from Teradata and Customer Hub (Oracle).
    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
    IBM
    • Enterprise reporting - Create, customise, and run reports on sales trends, consumer sentiment, etc.
    • Dashboard creation and data exploration & analysis - Using drag and drop feature to create ad-hoc visualisation. Additionally, using AI powered natural language query feature for data analysis and dashboard input (formation of pie, bar, line charts). It's useful for no-technical person to put queries around the spreadsheet data to get quick answers.
    • Building insights for accurate decision making - Package reports with data backed insights for stakeholders in pdf, and Excel format to support business ad-hoc cases, forecasting and strategic recommendations on relevant asks.
    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
    IBM
    • IBM Cognos Analytics enables customer data segmentation, which is essential for marketing, improving and streamlining purchasing behavior and preferences. This helps companies create more targeted and effective marketing campaigns.
    • Our clients Through data analysis, we can identify and observe trends in the behavior of other clients, allowing us to anticipate needs and adjust strategies to avoid consequences.
    Incentivized
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    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
    IBM
    For an existing solution, renewing licenses does provide a good return on investment. Additionally, while rolling out scorecards and dashboards with little adhoc capabilities, to end users, cognos is very easily scalable. It also allows to create a solution that has a mix of OLAP and relational data-sources, which is a limitation with other tools. Synchronizing with existing security setup is easy too.
    Read full review
    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
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    IBM
    We have a strong user base (3500 users) that are highly utilizing this tool. Basic users are able to consume content within the applied security model. We have a set of advanced users that really push the limits of Cognos with Report and Query Studio. These users have created a lot of personal content and stored it in 'My Reports'. Users enjoy this flexibility.
    Read full review
    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
    IBM
    Reports can typically be viewed through any browser that can access the server, so the availability is ultimately up to what the company utilizing it is comfortable with allowing, though report development tends to be more picky about browsers and settings as mentioned above. It also has an optional iPad app and general mobile browsing support, but dashboards lack the mobile compatibility. What keeps it from getting a higher score is the desktop tools that are vital to the development process. The compatibility with only Windows when the server has a wide range of compatibility can be a real sore point for a company that outfits its employees exclusively with Mac or Linux machines. Of course, if they are planning on outsourcing the development anyways, it's a rather moot point
    Read full review
    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
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    IBM
    Overall no major complaints but it doesn't handle DMR (Dimensionally Modeled for Relational) very well. DMR modelling is a capability that IBM Cognos Framework Manager provides allowing you to specify dimensional information for relational metadata and allows for OLAP-style queries. However, the capability is not very efficient and, for example, if I'm using only 2 columns on a 20-column model, the software is not smart enough to exclude 18 columns and the query side gets progressively larger and larger until it's effectively unusable.
    Read full review
    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
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    IBM
    Why is their web application not working as fast as you think it should? They never know, and it is always a a bunch of shots in the dark to find out. Trying to download software from them is like trying to find a book at the library before computers were invented.
    Incentivized
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    In-Person Training
    Google
    No answers on this topic
    IBM
    Onsite training provided by IBM Cognos was effective and as expected. They did not perform training with our data which was a bit difficult for our end-users.
    Read full review
    Online Training
    Google
    No answers on this topic
    IBM
    The online courses they offer are thorough and presented in such a way that someone who isn't already familiar with the general design methodologies used in this field will be capable of making a good design. The training environments are provided as a fully self contained virtual machine with everything needed already to create the environments. We've had some persisting issues with the environments becoming unavailable, but support has been responsive when these issues arise and straightening them out for us
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    IBM
    Make sure that any custom tables that you have, are built into your metadata packages. You can still access them via SQL queries in Cognos, but it is much easier to have them as a part of the available metadata packages.
    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
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    IBM
    Power BI is stronger for quick ad-hoc analysis and dashboards, but IBM Cognos Analytics is better when consistency, precision, and mass distribution matter. Tableau is best for interactive analysis, while IBM Cognos Analytics is better for standardized, repeatable enterprise reporting. Sigma shines for customizable dashboards and drill-down analysis while IBM Cognos Analytics holds an edge in data discovery and visualization.
    Incentivized
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    Contract Terms and Pricing Model
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    IBM
    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
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    IBM
    We rate IBM Cognos Analytics a 9 out of 10 for overall scalability. The platform handles large numbers of users, reports, and analytical workloads very reliably. We have experienced strong performance even in demanding enterprise environments with substantial data volumes. Its architecture provides sufficient flexibility to scale resources according to demand, making it well suited for large, business-critical deployments.
    Incentivized
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    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
    IBM
    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
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    IBM
    • The platform can be pretty pricey.
    • Convoluted contracts and they fine you for any breach during audits.
    • Things are changed between releases without any warning and break.
    • It is second to none at being able to customize list and crosstab type reports.
    • You can easily set up a report to be emailed out every day and even have it export the report to a shared folder.
    • On-prem environments can be scaled up pretty much as much as you would like.
    Incentivized
    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.

    IBM Cognos Analytics Screenshots

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