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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Db2

    Score8.6 out of 10
    N/ADB2 is a family of relational database software solutions offered by IBM. It includes standard Db2 and Db2 Warehouse editions, either deployable on-cloud, or on-premise.

    $0

    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
    Db2Google BigQuery
    Editions & Modules
    Db2 on Cloud Lite
    $0
    Db2 on Cloud Standard
    $99
    per month
    Db2 Warehouse on Cloud Flex One
    $898
    per month
    Db2 on Cloud Enterprise
    $946
    per month
    Db2 Warehouse on Cloud Flex for AWS
    2,957
    per month
    Db2 Warehouse on Cloud Flex
    $3,451
    per month
    Db2 Warehouse on Cloud Flex Performance
    13,651
    per month
    Db2 Warehouse on Cloud Flex Performance for AWS
    13,651
    per month
    Db2 Standard Edition
    Contact Sales
    Db2 Advanced Edition
    Contact Sales
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Offerings
    Pricing Offerings
    Db2Google BigQuery
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    YesNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional Details
    More Pricing Information
    Community Pulse
    Db2Google BigQuery
    Considered Both Products
    IBM
    Chose Db2
    Tried tested true and dependable. Main distinguishing factor however is the ongoing time in which it has been relied on, the preference by some stakeholders for ensuring sensitive data security, and its flexibility
    Incentivized
    Google
    No answer on this topic
    Key User Insights
    Would buy again
    96%
    Would buy again
    103 Answers
    98%
    Would buy again
    64 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    95 Answers
    97%
    Delivers good value for the price
    56 Answers
    Happy with the feature set
    96%
    Happy with the feature set
    103 Answers
    97%
    Happy with the feature set
    63 Answers
    Lived up to sales and marketing promises
    96%
    Lived up to sales and marketing promises
    66 Answers
    100%
    Lived up to sales and marketing promises
    42 Answers
    Implementation went as expected
    99%
    Implementation went as expected
    89 Answers
    100%
    Implementation went as expected
    59 Answers
    Features
    Db2Google BigQuery
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Db2 and Google BigQuery
    Feature
    Db2
    -
    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
    Db2Google BigQuery
    Small Businesses
    Amazon RDS
    Score8.1 out of 10
    MongoDB Atlas
    Score7.8 out of 10
    Medium-sized Companies
    SingleStore
    Score8.2 out of 10
    Azure Database
    Score8.8 out of 10
    Enterprises
    SAP IQ
    Score5.5 out of 10
    Google Cloud SQL
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Db2Google BigQuery
    Likelihood to Recommend
    9.1
    (114 ratings)
    9.0
    (79 ratings)
    Likelihood to Renew
    7.9
    (12 ratings)
    8.1
    (5 ratings)
    Usability
    8.5
    (9 ratings)
    6.6
    (6 ratings)
    Availability
    9.3
    (64 ratings)
    7.3
    (1 ratings)
    Performance
    9.1
    (12 ratings)
    6.4
    (1 ratings)
    Support Rating
    8.9
    (6 ratings)
    4.8
    (11 ratings)
    In-Person Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    5.6
    (3 ratings)
    -
    (0 ratings)
    Configurability
    9.1
    (2 ratings)
    6.4
    (1 ratings)
    Contract Terms and Pricing Model
    -
    (0 ratings)
    10.0
    (1 ratings)
    Data Sharing and Collaboration
    8.0
    (1 ratings)
    -
    (0 ratings)
    Data Sources
    9.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    7.8
    (4 ratings)
    7.3
    (1 ratings)
    Product Scalability
    8.4
    (66 ratings)
    7.3
    (1 ratings)
    Professional Services
    -
    (0 ratings)
    8.2
    (2 ratings)
    Vendor post-sale
    9.0
    (2 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    9.0
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Db2Google BigQuery
    Likelihood to Recommend
    IBM
    I have primarily used it as the basis for a SIS - but I have migrated more than a few systems from there database systems to DB2 (Filemaker, MySQL, etc.). DB2 does have a better structural approach, as opposed to Filemaker, which allows for more data consistency, but this can also lead to an inflexibility that can sometimes be counterintuitive when attempting to compensate for the flexibility of the work environment as Schools tend to have an all in one approach.
    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
    IBM
    • While we query a large set of data, the results are generally available within a minute or so.
    • Always reliable - I have never experienced an application going down.
    • It is easy to write queries and find tables and columns.
    • We can log in smoothly without any headaches.
    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
    IBM
    • Learning curve for DB resources - Improvements to UI or native command line built-ins can help with increasing efficiencies for DB resources
    • Better resource utilization monitoring and recommendations
    • Continue to adopt support for modern frameworks and languages making it easier for organizations to see making Db2 the easy first choice
    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
    IBM
    The DB2 database is a solid option for our school. We have been on this journey now for 3-4 years so we are still adapting to what it can do. We will renew our use of DB2 because we don’t see. Major need to change. Also, changing a main database in a school environment is a major project, so we’ll avoid that if possible.
    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
    IBM
    You have to be well versed in using the technology, not only from a GUI interface but from a command line interface to successfully use this software to its fullest.
    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
    IBM
    I have never had DB2 go down unexpectedly. It just works solidly every day. When I look at the logs, sometimes DB2 has figured out there was a need to build an index. Instead of waiting for me to do it, the database automatically created the index for me. At my current company, we have had zero issues for the past 8 years. We have upgrade the server 3 times and upgraded the OS each time and the only thing we saw was that DB2 got better and faster. It is simply amazing.
    Incentivized
    Read full review
    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
    Performance
    IBM
    The performances are exceptional if you take care to maintain the database. It is a very powerful tool and at the same time very easy to use. In our installation, we expect a DB machine on the mainframe with access to the database through ODBC connectors directly from branch servers, with fabulous end users experience.
    Incentivized
    Read full review
    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
    Support Rating
    IBM
    Easily the best product support team. :) Whenever we have questions, they have answered those in a timely manner and we like how they go above and beyond to help.
    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
    Read full review
    In-Person Training
    IBM
    the material was very clear and all subjects have been handled
    Incentivized
    Read full review
    Google
    No answers on this topic
    Implementation Rating
    IBM
    db2 work well with the application, also the replication tool can keep it up
    Read full review
    Google
    No answers on this topic
    Alternatives Considered
    IBM
    DB2 was more scalable and easily configurable than other products we evaluated and short listed in terms of functionality and pricing. IBM also had a good demo on premise and provided us a sandbox experience to test out and play with the product and DB2 at that time came out better than other similar products.
    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
    IBM
    No answers on this topic
    Google
    None so far. Very satisfied with the transparency on contract terms and pricing model.
    Read full review
    Scalability
    IBM
    By
    using DB2 only to support my IzPCA activities, my knowledge here
    is somewhat limited.

    Anyway,
    from what I was able to understand, DB2 is extremely scallable.

    Maybe the information below could serve as an example of scalability.
    Customer have an huge mainframe environment, 13x z15 CECs, around
    80 LPARs, and maybe more than 50 Sysplexes (I am not totally sure about this
    last figure...)

    Today
    we have 7 IzPCA
    databases, each one in a distinct Syplex.

    Plans
    are underway to have, at the end, an small LPAR, with only one DB2 sub-system,
    and with only one database, then transmit the data from a lot of other LPARs,
    and then process all the data in this only one database.



    The
    IzPCA collect process (read the data received, manipulate it, and insert rows
    in the tables) today is a huge process, demanding many elapsed
    hours, and lots of CPU.

    Almost
    100% of the tables are PBR type, insert jobs run in parallel, but in 4 of the 7
    database, it is a really a huge and long process.



    Combining
    the INSERTs loads from the 7 databases in only one will be impossible.......,,,,



    But,
    IzPCA recently introduced a new feature, called "Continuous
    Collector"
    .
    By
    using that feature, small amounts of data will be transmited to the central
    LPAR at every 5 minutes (or even less), processed immediately,in
    a short period of time, and with small use of CPU,
    instead of one or two transmissions by day, of very large amounts of data and
    the corresponding collect jobs occurring only once or twice a day, with long
    elapsed times, and huge comsumption of CPU



    I
    suspect the total CPU seconds consumed will be more or less the same in
    both cases, but in the new method it will occur in small bursts
    many times a day!!
    Incentivized
    Read full review
    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
    IBM
    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
    IBM
    • Negative: Difficult and manual deployment
    • Negative: Missing assistants from common monitoring metrics
    • Positive: Stability
    • Positive: Performance
    • Positive: Resiliency and high availability (HADR)
    • Positive: Data Replication (Q-Rep)
    • Positive: Interaction with storage subsystems for backups (TSM, SVC)
    • Positive: Gigantic monitoring features in the form of table functions
    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

    Db2 Screenshots

    Screenshot of Db2 - Data sharingScreenshot of Db2 - Machine LearningScreenshot of Db2 - Real time insights

    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.