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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)

    Liquibase

    Score8.7 out of 10
    Enterprise companies (1,001+ employees)
    Liquibase is a database change management tool that extends DevOps best practices to the database, helping teams release software faster and safer by bringing the database change process into existing CI/CD automation. According to the 2021 Accelerate State of DevOps Report, elite performers are 3.4 times more likely to incorporate database change management into their process than low performers. Liquibase value proposition: Liquibase speeds up the development…N/A
    Pricing
    Google BigQueryLiquibase
    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 BigQueryLiquibase
    Free Trial
    YesYes
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryLiquibase
    Considered Both Products
    Google
    No answer on this topic
    Liquibase
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    64 Answers
    94%
    Would buy again
    68 Answers
    Delivers good value for the price
    97%
    Delivers good value for the price
    56 Answers
    97%
    Delivers good value for the price
    59 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    63 Answers
    94%
    Happy with the feature set
    68 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    42 Answers
    95%
    Lived up to sales and marketing promises
    41 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    59 Answers
    94%
    Implementation went as expected
    62 Answers
    Features
    Google BigQueryLiquibase
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Liquibase
    Feature
    Google BigQuery
    8.5
    80 Ratings
    1% above category average
    Liquibase
    -
    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
    Best Alternatives
    Google BigQueryLiquibase
    Small Businesses
    MongoDB Atlas
    Score7.8 out of 10
    No answers on this topic
    Medium-sized Companies
    Azure Database
    Score8.8 out of 10
    Redgate SQL Toolbelt Essentials
    Score9.6 out of 10
    Enterprises
    Google Cloud SQL
    Score8.7 out of 10
    Redgate SQL Toolbelt Essentials
    Score9.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryLiquibase
    Likelihood to Recommend
    9.0
    (79 ratings)
    9.2
    (70 ratings)
    Likelihood to Renew
    8.1
    (5 ratings)
    9.1
    (4 ratings)
    Usability
    6.6
    (6 ratings)
    8.0
    (3 ratings)
    Availability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Performance
    6.4
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    4.8
    (11 ratings)
    8.8
    (69 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.1
    (2 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 BigQueryLiquibase
    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
    Liquibase
    Based on my experience so far on using Liquibase in my current project, I have seen that Liquibase changelogs are version control where multiple team members and developers can work together on database and deployed automatically via CI/CD Pipeline integration using github actions and it applies same changelogs to all enviroments to remain in sync and avoid any enviroment drift. Also as Liquibase stores changelog audits in DATABASECHANGELOG table it helps in tracking purposes and to easily rollback any change . Whereas in some scenarios I feel that Liquibase have some drawbacks where if complex transformation between tables is not optimized for bulk data operations which eventually degrades database performance.
    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
    Liquibase
    • Liquibase tracks changes in a metadata table contained directly in the target database, making easy administration for the DBA.
    • Liquibase handles many validation tests out of the box, making it easy to choose which ones you want to include, with options for writing your own if you choose. This makes it robust and flexible in terms of validation before deployment.
    • Liquibase provides easy integration into deployment pipelines for CI/CD. We use it with GitHub for source control and Circle CI for validation and deployment pipelines.
    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
    Liquibase
    • I would like Liquibase to explore all errors in the changelog files compared to one at a time. We spent a lot of time troubleshooting one error at a time versus having a batch log of errors in each file.
    • Understanding where to get support on things. I spent a lot of time researching externally to learn what the best practices were. Although I found some of the youtube videos helpful, I would like a little more of a technical support. This may be a feature with the paid tier, however, we leveraged open source.
    • Seeing more examples of how others use Liquibase and their usecases will be helpful. That way we can learn from each other which may help us improve on our own deployments.
    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
    Liquibase
    We are and will continue using Liquibase and it has become an integral part of our portfolio offering, any new product is by default adopting Liquibase stack.
    Incentivized
    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
    Read full review
    Liquibase
    Liquibase has several features, on their free plan, that matches exactly our expectations and needs: this already makes it standout from its competitors. On top of that, the setup was straightforward: we are running an integration with Databricks, and there were only two steps truly needed, install the driver and the plugin, done. This is the type of seamless experience our team appreciates the most when evaluating a tool or service.
    Incentivized
    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
    Liquibase
    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
    Liquibase
    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
    Liquibase
    Liquibase has been responsive and even is letting our group test some new products they are developing and even made code changes to their production system because of a couple bugs we have reported. Liquibase licensing has also been easy and simple. I have nothing bad to say about any of the Liquibase staff I have talked to. They also hold free information webinars for new content that helps spread adoption and moving the product forward.
    Incentivized
    Read full review
    Implementation Rating
    Google
    No answers on this topic
    Liquibase
    Build process takes a toll.
    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
    Liquibase
    There is no real competitor when it comes to what Liquibase does - at least not at the time we considered it three years ago. It was an easy choice in this regard, but we could have said no to it if it made our workload more difficult. But our proof of concept showed there were easy wins to be had by implementing its software.
    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
    Liquibase
    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
    Liquibase
    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
    Liquibase
    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
    Liquibase
    • We need to re-educate developers to use Liquibase.
    • In some cases, it is hard to align when several teams work on the same DB.
    • On the other hand, Liquibase provides order and consistency in managing DB changes.
    • Evidence and traceability are a plus.
    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.