What users are saying about

Apache Spark vs Google BigQuery

Apache Spark
145 Ratings
Google BigQuery
173 Ratings

Apache Spark

145 Ratings
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Score 8.8 out of 100

Based on 145 reviews and ratings

Google BigQuery

173 Ratings
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Score 9 out of 100

Based on 173 reviews and ratings

Feature Set Ratings

    Database-as-a-Service

    Apache Spark

    Feature Set Not Supported
    N/A
    9.2

    Google BigQuery

    92%
    Google BigQuery ranks higher in 6/6 features
    Google BigQuery ranks higher in 6/6 features

    Automatic software patching

    N/A
    0 Ratings
    9.2
    92%
    17 Ratings

    Database scalability

    N/A
    0 Ratings
    9.8
    98%
    29 Ratings

    Automated backups

    N/A
    0 Ratings
    9.4
    94%
    24 Ratings

    Database security provisions

    N/A
    0 Ratings
    9.2
    92%
    24 Ratings

    Monitoring and metrics

    N/A
    0 Ratings
    8.3
    83%
    25 Ratings

    Automatic host deployment

    N/A
    0 Ratings
    9.2
    92%
    14 Ratings

    Attribute Ratings

    • Google BigQuery is rated higher in 3 areas: Likelihood to Recommend, Usability, Support Rating

    Likelihood to Recommend

    9.2

    Apache Spark

    92%
    22 Ratings
    9.6

    Google BigQuery

    96%
    29 Ratings

    Likelihood to Renew

    10.0

    Apache Spark

    100%
    1 Rating

    Google BigQuery

    N/A
    0 Ratings

    Usability

    9.4

    Apache Spark

    94%
    2 Ratings
    9.5

    Google BigQuery

    95%
    3 Ratings

    Support Rating

    8.7

    Apache Spark

    87%
    6 Ratings
    9.7

    Google BigQuery

    97%
    18 Ratings

    Contract Terms and Pricing Model

    Apache Spark

    N/A
    0 Ratings
    10.0

    Google BigQuery

    100%
    1 Rating

    Professional Services

    Apache Spark

    N/A
    0 Ratings
    8.5

    Google BigQuery

    85%
    2 Ratings

    Likelihood to Recommend

    Apache Spark

    The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.

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    Thomas Young | TrustRadius Reviewer
    Thomas Young
    View all 22 answers on this topic

    Google BigQuery

    If you are using Google suites like Analytics 360, Big Query can be a very useful tool for storing & querying your data because of its seem less integration within Google environment. Also if your organisation has large set of data and you want fast data processing, then only it makes sense to move to Google BigQuery otherwise there are cheaper alternatives available.

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    Sameera Srivastava | TrustRadius Reviewer
    Sameera Srivastava
    View all 29 answers on this topic

    Pros

    Apache Spark

    • Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
    • Faster in execution times compare to Hadoop and PIG Latin
    • Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
    • Interoperability between SQL and Scala / Python style of munging data

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    Nitin Pasumarthy | TrustRadius Reviewer
    Nitin Pasumarthy
    View all 22 answers on this topic

    Google BigQuery

    • Huge plus point if you have idea running SQL scripts.
    • The ability to store and manage multiple data warehouses is a big plus point which helps a lot for growing businesses.
    • Easy integration with tools like Data Studio and Google Analytics which provides great data warehouse and data management solutions.

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    Rounak Verma | TrustRadius Reviewer
    Rounak Verma
    View all 29 answers on this topic

    Cons

    Apache Spark

    • Memory management. Very weak on that.
    • PySpark not as robust as scala with spark.
    • spark master HA is needed. Not as HA as it should be.
    • Locality should not be a necessity, but does help improvement. But would prefer no locality

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    Anson Abraham | TrustRadius Reviewer
    Anson Abraham
    View all 22 answers on this topic

    Google BigQuery

    • One issue with Google Cloud Storage is its price. For one to have that premium Google Cloud Storage, for the purpose of massive storage, he/she must have adequate cash. Otherwise, Google Cloud Storage is a safe and perfect online storage platform.
    • The only thing that can come to mind that would be annoying with this software was that sometimes when trying to share files on the Cloud with coworkers, it would just not share at all, or there would be a massive delay in when I shared them and when they received them. Other than that though, everything is perfect with this.

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    Sam Lepak | TrustRadius Reviewer
    Sam Lepak
    View all 29 answers on this topic

    Pricing Details

    Apache Spark

    General

    Free Trial
    —
    Free/Freemium Version
    —
    Premium Consulting/Integration Services
    —
    Entry-level set up fee?
    No

    Starting Price

    —

    Apache Spark Editions & Modules

    —
    Additional Pricing Details
    —

    Google BigQuery

    General

    Free Trial
    —
    Free/Freemium Version
    —
    Premium Consulting/Integration Services
    —
    Entry-level set up fee?
    No

    Starting Price

    $4 per 100 slots

    Google BigQuery Editions & Modules

    Edition
    Queries (On-Demand)$51
    Queries (Hourly Flex Slots)$42
    Queries (Monthly Flat Rate)$20002
    Queries (Annual Flat Rate)$1,7002
    1. per TB
    2. per 100 slots
    Additional Pricing Details
    —

    Likelihood to Renew

    Apache Spark

    Apache Spark 10.0
    Based on 1 answer
    Capacity of computing data in cluster and fast speed.

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    Steven Li | TrustRadius Reviewer
    Steven Li
    View all 1 answers on this topic

    Google BigQuery

    No score
    No answers yet
    No answers on this topic

    Usability

    Apache Spark

    Apache Spark 9.4
    Based on 2 answers
    The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.

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    Anonymous | TrustRadius Reviewer
    Verified User
    View all 2 answers on this topic

    Google BigQuery

    Google BigQuery 9.5
    Based on 3 answers
    web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2

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    Richard Atkins | TrustRadius Reviewer
    Richard Atkins
    View all 3 answers on this topic

    Support Rating

    Apache Spark

    Apache Spark 8.7
    Based on 6 answers
    1. It integrates very well with scala or python.2. It's very easy to understand SQL interoperability.3. Apache is way faster than the other competitive technologies.4. The support from the Apache community is very huge for Spark.5. Execution times are faster as compared to others.6. There are a large number of forums available for Apache Spark.7. The code availability for Apache Spark is simpler and easy to gain access to.8. Many organizations use Apache Spark, so many solutions are available for existing applications.

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    Yogesh Mhasde | TrustRadius Reviewer
    Yogesh Mhasde
    View all 6 answers on this topic

    Google BigQuery

    Google BigQuery 9.7
    Based on 18 answers
    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.

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    Tristan Dobbs | TrustRadius Reviewer
    Tristan Dobbs
    View all 18 answers on this topic

    Alternatives Considered

    Apache Spark

    Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.

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    Anonymous | TrustRadius Reviewer
    Verified User
    View all 22 answers on this topic

    Google BigQuery

    Spinning up, provisioning, maintaining and debugging a Hadoop solution can be non-trivial, painful. I'm talking about both GCE based or HDInsight clusters. It requires expertise (+ employee hire, costs). With BigQuery if someone has a good SQL knowledge (and maybe a little programming), can already start to test and develop. All of the infrastructure and platform services are taken care of. Google BigQuery is a magnitudes simpler to use than Hadoop, but you have to evaluate the costs. BigQuery billing is dependent on your data size and how much data your query touches.

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    Csaba Toth | TrustRadius Reviewer
    Csaba Toth
    View all 29 answers on this topic

    Contract Terms and Pricing Model

    Apache Spark

    No score
    No answers yet
    No answers on this topic

    Google BigQuery

    Google BigQuery 10.0
    Based on 1 answer
    None so far. Very satisfied with the transparency on contract terms and pricing model.

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    Anonymous | TrustRadius Reviewer
    Verified User
    View all 1 answers on this topic

    Professional Services

    Apache Spark

    No score
    No answers yet
    No answers on this topic

    Google BigQuery

    Google BigQuery 8.5
    Based on 2 answers
    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.

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    Anonymous | TrustRadius Reviewer
    Verified User
    View all 2 answers on this topic

    Return on Investment

    Apache Spark

    • Business leaders are able to take data driven decisions
    • Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
    • Business is able come up with new product ideas

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    Surendranatha Reddy Chappidi | TrustRadius Reviewer
    Surendranatha Reddy Chappidi
    View all 22 answers on this topic

    Google BigQuery

    • Google BigQuery has had enormous impact in terms of ROI to our business, as it has allowed us to ease our dependence on our physical servers, which we pay for monthly from another hosting service. We have been able to run multiple enterprise scale data processing applications with almost no investment
    • Since our business is highly client focused, Google Cloud Platform, and BigQuery specifically, has allowed us to get very granular in how our usage should be attributed to different projects, clients, and teams.
    • Plain and simple, I believe the meager investments that we have made in Google BigQuery have paid themselves back hundreds of times over.

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    Alex Andrews | TrustRadius Reviewer
    Alex Andrews
    View all 29 answers on this topic

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