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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    FactSet Workstation

    Score8.5 out of 10
    N/AThe FactSet Workstation is a dynamic platform designed to empower financial professionals with seamless data access, advanced analytics, and technology. Integrating over 800 data sources across asset classes and markets, it consolidates crucial insights and elevates decision-making. Its AI-powered tools include smart search and chat features. The workstation simplifies complex workflows, enabling users to uncover insights quickly and improve collaboration. From research and portfolio…N/A

    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)

    Pricing
    FactSet WorkstationGoogle BigQuery
    Editions & Modules
    No answers on this topic
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Offerings
    Pricing Offerings
    FactSet WorkstationGoogle BigQuery
    Free Trial
    YesYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeRequiredNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    FactSet WorkstationGoogle BigQuery
    Considered Both Products
    FactSet
    No answer on this topic
    Google
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    16 Answers
    98%
    Would buy again
    64 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    15 Answers
    97%
    Delivers good value for the price
    56 Answers
    Happy with the feature set
    94%
    Happy with the feature set
    15 Answers
    97%
    Happy with the feature set
    63 Answers
    Lived up to sales and marketing promises
    92%
    Lived up to sales and marketing promises
    12 Answers
    100%
    Lived up to sales and marketing promises
    42 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    11 Answers
    100%
    Implementation went as expected
    59 Answers
    Features
    FactSet WorkstationGoogle BigQuery
    Financial Research
    Comparison of Financial Research features of FactSet Workstation and Google BigQuery
    Feature
    FactSet Workstation
    6.6
    13 Ratings
    11% below category average
    Google BigQuery
    -
    Ratings
    Private Company Data4.710 Ratings00 Ratings
    Industry-Specific Information6.913 Ratings00 Ratings
    Independent Research Access6.912 Ratings00 Ratings
    M&A Analysis6.210 Ratings00 Ratings
    Supply Chain Data5.98 Ratings00 Ratings
    ESG Data6.29 Ratings00 Ratings
    Macroeconomic News7.813 Ratings00 Ratings
    Search Tools7.813 Ratings00 Ratings
    Database-as-a-Service
    Comparison of Database-as-a-Service features of FactSet Workstation and Google BigQuery
    Feature
    FactSet Workstation
    -
    Ratings
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Automatic software patching00 Ratings8.017 Ratings
    Database scalability00 Ratings9.079 Ratings
    Automated backups00 Ratings8.524 Ratings
    Database security provisions00 Ratings8.873 Ratings
    Monitoring and metrics00 Ratings8.675 Ratings
    Automatic host deployment00 Ratings8.013 Ratings
    Best Alternatives
    FactSet WorkstationGoogle BigQuery
    Small Businesses
    No answers on this topic
    MongoDB Atlas
    Score7.8 out of 10
    Medium-sized Companies
    S&P Capital IQ
    Score7.5 out of 10
    Azure Database
    Score8.8 out of 10
    Enterprises
    S&P Capital IQ
    Score7.5 out of 10
    Google Cloud SQL
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    FactSet WorkstationGoogle BigQuery
    Likelihood to Recommend
    8.5
    (17 ratings)
    9.0
    (79 ratings)
    Likelihood to Renew
    10.0
    (2 ratings)
    8.1
    (5 ratings)
    Usability
    7.1
    (13 ratings)
    6.6
    (6 ratings)
    Availability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Performance
    -
    (0 ratings)
    6.4
    (1 ratings)
    Support Rating
    7.0
    (1 ratings)
    4.8
    (11 ratings)
    Configurability
    -
    (0 ratings)
    6.4
    (1 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    10.0
    (1 ratings)
    Ease of integration
    -
    (0 ratings)
    7.3
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Professional Services
    -
    (0 ratings)
    8.2
    (2 ratings)
    User Testimonials
    FactSet WorkstationGoogle BigQuery
    Likelihood to Recommend
    FactSet
    FactSet works for all my IR needs. I do not see a function for which I use it for that it would be less appropriate. I believe that the tool's efforts towards becoming more integrated with AI are strong and that in time the Mercury offering will be just as competitive as some of the other AI offerings out there today such as AlphaSense
    Incentivized
    Read full review
    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
    Pros
    FactSet
    • Easy/clear UI for navigation
    • Easily find and sort through financial filings to get to the data
    • Document search functionality seems to be improving consistently with more robust features
    Incentivized
    Read full review
    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
    Cons
    FactSet
    • The user interface on stock monitor needs work - sometimes I wish to clone the same fields to another tab/watchlist and it appears the best way to do so is recreate it form scratch
    • transcript to be more timely and more accurate
    • on the consensus financial forecast tab, have more segment breakouts like Visible Alpha
    Incentivized
    Read full review
    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
    Likelihood to Renew
    FactSet
    We need the FactSet data and capabilities to complete 75% of the financial analyses that we complete for both internal and external purposes. It is invaluable and I am not aware of any other provider that would be able to fill this gap that FactSet does
    Incentivized
    Read full review
    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
    Usability
    FactSet
    It does everything I need. It is pretty user friendly and easy to work with whatever technology interface I am using (desk top, notebook, tablet, or mobile phone). I am able to get work done whether I am in the office, at home, or traveling. The user up time is very good. They are rarely doing maintenance when I need to use the platform
    Incentivized
    Read full review
    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
    Reliability and Availability
    FactSet
    No answers on this topic
    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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    Performance
    FactSet
    No answers on this topic
    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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    Support Rating
    FactSet
    I think the data delivery could be improved, but it's a good data set.
    Incentivized
    Read full review
    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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    Alternatives Considered
    FactSet
    Product is magnitudes more affordable and provides 80% of the functionality that Bloomberg has and is working to build out the remaining. The workstation is more user friendly than bloomberg but still not perfect. Not as robust as a Bloomberg Terminal and doesn't have the chat/trading features.
    Incentivized
    Read full review
    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
    Contract Terms and Pricing Model
    FactSet
    No answers on this topic
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Scalability
    FactSet
    No answers on this topic
    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
    Professional Services
    FactSet
    No answers on this topic
    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
    Return on Investment
    FactSet
    • hard to quantify, bc i havent brought any new business bc of it, so the ROI would be 0%. I use other systems for proposals.
    • However, I use it for everyday work and equity/fi analysis and portfolio construction research at ticker level, and that part works 100%.
    Incentivized
    Read full review
    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
    ScreenShots

    FactSet Workstation Screenshots

    Screenshot of PM Hub, which simplifies portfolio management with tools for building, analyzing, and simulating trades for multi-asset class portfolios and exposures. Users can monitor positions in real time with customizable views, ensure compliance, and execute trades through its integration. Link IRN data to foster deeper collaboration between research analysts and portfolio managers.Screenshot of FactSet Internal Research Notes (IRN), which streamlines research with one connected platform. These can be used to organize, share, and analyze everything from market trends to individual securities. Its AI tools help to boost collaboration, enhance workflows, and drive smarter investment decisions.Screenshot of some of the available information which can used to analyze performance, risk, and attribution across multi-asset portfolios. This integrates portfolio, market, and proprietary data into a single platform to streamline workflows, adapt to market changes, and make confident decisions. From stress testing and scenario analysis to AI-driven insights, FactSet provides tools to strengthen portfolio resilience, uncover drivers of performance, and foster collaboration with customizable reports and data sharing.Screenshot of a display of all accounts in one personalized dashboard. Viewers can analyze top positions, spot trends with proprietary signals, and track market-moving events. Access summary stats like total market value and asset allocation across an entire book or by household and strategy.Screenshot of FactSet’s proprietary news, which delivers real-time, focused market insights across regions like the U.S., Canada, Europe, and Asia-Pacific. From stocks to sectors to broad markets, StreetAccount simplifies updates to cut through the clutter. This critical news is available anytime via the Workstation, web, email, app, or API.Screenshot of one of FactSet's unique datasets, Geographic Revenue (GeoRev), used to quickly understand a company's revenue exposure in countries impacted by geopolitical, macroeconomic, and market risk through a highly structured and normalized display of companies' revenues by geography.

    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.