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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 Guardium

    Score9.1 out of 10
    N/AIBM Guardium is IBM's data security posture management solution, that aims to offer organizations comprehensive visibility, actionable insights and real-time controls to help users comply with regulations, preserve privacy and secure sensitive data no matter where it is stored.N/A
    Pricing
    Google BigQueryIBM Guardium
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    No answers on this topic
    Offerings
    Pricing Offerings
    Google BigQueryIBM Guardium
    Free Trial
    YesYes
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—Pricing is dependent based on data source environment.
    More Pricing Information
    Community Pulse
    Google BigQueryIBM Guardium
    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
    99%
    Would buy again
    77 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    97%
    Delivers good value for the price
    61 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    94%
    Happy with the feature set
    73 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    94%
    Lived up to sales and marketing promises
    50 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    95%
    Implementation went as expected
    63 Answers
    Features
    Google BigQueryIBM Guardium
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and IBM Guardium
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    IBM Guardium
    -
    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
    Data Security Posture Management (DSPM)
    Comparison of Data Security Posture Management (DSPM) features of Google BigQuery and IBM Guardium
    Feature
    Google BigQuery
    -
    Ratings
    IBM Guardium
    8.1
    1 Ratings
    0% above category average
    Shadow & Dark Data Identification00 Ratings7.31 Ratings
    Data Access & Entitlement Mapping00 Ratings8.21 Ratings
    Security Posture Assessment & Risk Prioritization00 Ratings9.11 Ratings
    Non-Intrusive, Agentless Scanning00 Ratings8.21 Ratings
    Data Lineage and Flow Tracking00 Ratings8.21 Ratings
    Automated Remediation Workflows00 Ratings8.21 Ratings
    Real-Time Data Detection and Response (DDR)00 Ratings8.21 Ratings
    AI-Ready Security Guardrails00 Ratings7.31 Ratings
    Automated Compliance Mapping00 Ratings8.21 Ratings
    Best Alternatives
    Google BigQueryIBM Guardium
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    No answers on this topic
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    No answers on this topic
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryIBM Guardium
    Likelihood to Recommend
    9.0
    (79 ratings)
    9.5
    (68 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    7.4
    (5 ratings)
    Usability
    6.6
    (6 ratings)
    5.6
    (34 ratings)
    Availability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.4
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    4.8
    (11 ratings)
    4.5
    (5 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)
    4.5
    (1 ratings)
    Product Scalability
    7.3
    (1 ratings)
    6.4
    (1 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Google BigQueryIBM Guardium
    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
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    IBM
    IBM Guardium DP is suitable for monitoring, auditing, data discovery, vulnerability analysis, and risk detection and investigation in relational and non-relational databases, cloud database services, indexed databases, and non-relational databases as well. IBM Guardium DPR is appropriate for supporting the process of detecting anomalous behavior in accessing sensitive data, helping to optimize the work of cybersecurity analysts or data team analysts by providing the data officer within our organization with insight into compromised users, compromised databases, or file servers containing sensitive data.
    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
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    IBM
    • Provides complete monitoring of data access and usage activities.
    • Provides customizable security controls and policies that help us meet compliance and regulatory requirements.
    • Uses advanced algorithms and machine learning to detect abnormal behavior patterns.
    • Helps us protect sensitive and confidential data by controlling access.
    • Integrates easily with other security systems and tools.
    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
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    IBM
    • Cleanup the menu bar- way too many items.
    • Ktap support for newer O/S. Recently, I have had to open support tickets to get the most recent support for the RHEL Kernel.
    • Also, upgrading agents to V12 doesnt not have the same Flex or exact match for KTAP as 11.5. You would think V12 would have the same Kernel support as 11.5. Clients are moving to V12.
    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
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    IBM
    It is a perfect system to detect problems that we do not see manually, it is light, with a very simple learning curve and with great protection of our data, we will use it forever.
    Incentivized
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    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
    This software is not the easiest to use in all work environments, each department has some difficulties accessing and managing some functions, it can be considered a complex softy, but I consider it necessary to have it in the company due to its security qualities of warm cans, it offers exactly what it promises but with a little difficulty in its configuration.
    Incentivized
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    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
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    IBM
    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
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    IBM
    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
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    IBM
    There has been great support coming from IBM. It is easy to use and a great way to keep our data secure. I would recommend this to other possible users and if I were to move companies, I would recommend we use this there too. Thank you
    Incentivized
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    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
    IBM Security Guardium has extended capabilities of automatically locating databases and assessing the vulnerabilities and configuration flaws in them. IBM Security Guardium stacks up against other products due to the additional features that can be easily added to your IT systems after installation. Additionally, Guardium has the ability to monitor a mainframe database environment which makes it the best choice!
    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
    Only a few users in our shop for now
    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
    • Security and monitoring are important in a financial institution
    • Constant visibility and auditing of companies is easy with IBM Guardium.
    • la seguridad y monitored es important en una entidad financiera
    • la visibilidad y auditoria constante de empresas es facil con IBM Guardium
    Incentivized
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    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 Guardium Screenshots

    Screenshot of the IBM Guardium Data Protection dashboard showing all the features. One click can take you to databases or to data analytics.Screenshot of IBM Guardium Data Protection: The S-TAP and GIM Dashboard gives real-time visibility into the health and performance of S-TAPs. It is used to track the status of different S-TAP versions, see database activity across inspection engines, and view detailed insights by operating system.Screenshot of IBM Guardium DSPM: Discovery, Classification & Threat Monitoring - Automate cloud data security with discovery, classification, and continuous threat monitoring. This offers a unified view of sensitive data across cloud workloads (AWS, Azure, GCP) and SaaS (SharePoint, OneDrive, Slack, Google Drive, Jira, Confluence and more), understand its risk level, and ensure ongoing protection and compliance.Screenshot of IBM Guardium DSPM: Discovery, Classification & Threat Monitoring - Automate cloud data security with discovery, classification, and continuous threat monitoring. This offers a unified view of sensitive data across cloud workloads (AWS, Azure, GCP) and SaaS (SharePoint, OneDrive, Slack, Google Drive, Jira, Confluence and more), understand its risk level, and ensure ongoing protection and compliance.Screenshot of IBM Guardium DSPM: Discovery, Classification & Threat Monitoring - Automate cloud data security with discovery, classification, and continuous threat monitoring. This offers a unified view of sensitive data across cloud workloads (AWS, Azure, GCP) and SaaS (SharePoint, OneDrive, Slack, Google Drive, Jira, Confluence and more), understand its risk level, and ensure ongoing protection and compliance.