TrustRadius: an HG Insights company

Save this comparison

Save this comparison

Add Product

Recommended Comparisons

    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Google BigQuery

    Score8.4 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)

    Oracle Exadata

    Score10 out of 10
    N/AOracle Exadata is an enterprise database platform that runs Oracle Database workloads of any scale and criticality with high performance, availability, and security. Exadata’s scale-out design employs optimizations that let transaction processing, analytics, machine learning, and mixed workloads run faster. Consolidating diverse Oracle Database workloads on Exadata platforms in enterprise data centers, Oracle Cloud Infrastructure (OCI), and multicloud environments helps organizations increase…

    $2.90

    Per Unit

    Pricing
    Google BigQueryOracle Exadata
    Editions & Modules
    Standard edition
    $0.04 / slot hour
    Enterprise edition
    $0.06 / slot hour
    Enterprise Plus edition
    $0.10 / slot hour
    Database Server
    $2.9032
    Per Unit
    Quarter Rack
    $14.5162
    Per Unit
    Offerings
    Pricing Offerings
    Google BigQueryOracle Exadata
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Google BigQueryOracle Exadata
    Considered Both Products
    Google
    No answer on this topic
    Oracle
    No answer on this topic
    Key User Insights
    Would buy again
    98%
    Would buy again
    51 Answers
    100%
    Would buy again
    5 Answers
    Delivers good value for the price
    96%
    Delivers good value for the price
    43 Answers
    100%
    Delivers good value for the price
    5 Answers
    Happy with the feature set
    96%
    Happy with the feature set
    50 Answers
    100%
    Happy with the feature set
    5 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    32 Answers
    100%
    Lived up to sales and marketing promises
    5 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    46 Answers
    100%
    Implementation went as expected
    5 Answers
    Features
    Google BigQueryOracle Exadata
    Database-as-a-Service
    Comparison of Database-as-a-Service features of Google BigQuery and Oracle Exadata
    Feature
    Google BigQuery
    8.4
    71 Ratings
    3% below category average
    Oracle Exadata
    -
    Ratings
    Automatic software patching8.017 Ratings00 Ratings
    Database scalability9.270 Ratings00 Ratings
    Automated backups8.524 Ratings00 Ratings
    Database security provisions8.664 Ratings00 Ratings
    Monitoring and metrics8.066 Ratings00 Ratings
    Automatic host deployment8.013 Ratings00 Ratings
    Access Control and Security
    Comparison of Access Control and Security features of Google BigQuery and Oracle Exadata
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Exadata
    10.0
    2 Ratings
    13% above category average
    Multi-User Support (named login)00 Ratings10.02 Ratings
    Multiple Access Permission Levels (Create, Read, Delete)00 Ratings10.02 Ratings
    Single Sign-On (SSO)00 Ratings10.01 Ratings
    Data Warehouse
    Comparison of Data Warehouse features of Google BigQuery and Oracle Exadata
    Feature
    Google BigQuery
    -
    Ratings
    Oracle Exadata
    9.3
    2 Ratings
    19% above category average
    High-Volume Data Processing00 Ratings10.02 Ratings
    Data Warehouse Management00 Ratings10.02 Ratings
    Administrative Automation00 Ratings7.02 Ratings
    Self-Optimization00 Ratings10.02 Ratings
    Best Alternatives
    Google BigQueryOracle Exadata
    Small Businesses
    MongoDB Atlas
    Score8.2 out of 10
    No answers on this topic
    Medium-sized Companies
    Azure Database
    Score9.8 out of 10
    Cloudera Enterprise Data Hub
    Score9 out of 10
    Enterprises
    Azure SQL Database
    Score8.9 out of 10
    Cloudera Enterprise Data Hub
    Score9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Google BigQueryOracle Exadata
    Likelihood to Recommend
    8.6
    (71 ratings)
    10.0
    (23 ratings)
    Likelihood to Renew
    8.1
    (3 ratings)
    -
    (0 ratings)
    Usability
    7.7
    (5 ratings)
    10.0
    (2 ratings)
    Support Rating
    7.3
    (10 ratings)
    -
    (0 ratings)
    Contract Terms and Pricing Model
    10.0
    (1 ratings)
    -
    (0 ratings)
    Professional Services
    8.2
    (2 ratings)
    -
    (0 ratings)
    User Testimonials
    Google BigQueryOracle Exadata
    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
    Oracle
    • First, get the database on Oracle. If you are in an Oracle stack, it would be much better to use the Oracle products. If you are driving a Ferrari, you wouldn’t put a Mercedes engine in it. If you are writing a query, you cannot rely on other brands. Since I'm an architect, when I look for a product, I look for performance.
    • The installation is easy because it comes out-of-the-box and you just start using it.
    • Previous to Oracle Exadata, we were using a normal Oracle RAC service. We were just waiting for this product to come out.
    • I'm currently writing a data warehouse on Exadata. Before this solution, we were aiming for this to be completed by 8 a.m., when our ETLs would finish. With the help of Exadata's special features, this was reduced to 3 a.m. This solution allows us to bring more data within the same time period. It provides us with more subject areas that provide more reports to our users. Our ETL times reduced to 65%, then to 50%.
    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
    Oracle
    • High speed of SQL operations due to a unique design of Exadata with offloading of SQL processing to storage cells
    • Built-in High Availability of a DB server due to it's base architecture of a multi-node Oracle Real Application Cluster
    • High overall sever performance due to its use of a proprietary "Smart Cache" feature utilizing a high speed flash memory
    • Excellent scalability of a DB server by adding cluster nodes as well as expanding it into a network of serially connected clusters
    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
    Oracle
    • Integrating with different types of databases can be a challenge
    • Having a hardware platform optimized to run specific database software surely comes with a price
    • Single vendor to support same hardware and software will make migrating to different hardware and/or software become a hassle
    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
    Oracle
    No answers on this topic
    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
    Oracle
    Excellent machine for your database needs . Don’t have to think twice if you have the budget to own it
    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
    Oracle
    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
    Oracle
    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
    Oracle
    No answers on this topic
    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
    Oracle
    Oracle Exadata Database Machine had the best performance overall hands down. It clearly beat the competition and we were seeing 1000X improvement on SAP HANA. Oracle Exadata Database Machine beat that without us refactoring our code. To achieve that in HANA, we had to refactor the code somewhat. Now this was for our limited POC of 5 use cases. Given the large number of stored procedures we had in Sybase, we need to capture more production metrics but we are seeing incredible performance.
    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
    Oracle
    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
    Oracle
    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
    Oracle
    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
    Oracle
    • Single support from a single vendor with both machine and database from Oracle, which is costing us less.
    • With Exadata, we need less technical manpower and less technical support. A business transaction with the integrated and centralized database helps us focus on other business needs.
    • We don't need to buy additional licenses and Hardware for the next 3 to 5 years.
    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.