What users are saying about
145 Ratings
228 Ratings
145 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 8.8 out of 100
228 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener'>trScore algorithm: Learn more.</a>
Score 8.1 out of 100

Feature Set Ratings

    Data Source Connection

    Apache Spark

    Feature Set Not Supported
    N/A
    6.3

    SSIS

    63%
    SQL Server Integration Services ranks higher in 2/2 features

    Connect to traditional data sources

    N/A
    0 Ratings
    8.6
    86%
    40 Ratings

    Connecto to Big Data and NoSQL

    N/A
    0 Ratings
    4.0
    40%
    30 Ratings

    Data Transformations

    Apache Spark

    Feature Set Not Supported
    N/A
    8.4

    SSIS

    84%
    SQL Server Integration Services ranks higher in 2/2 features

    Simple transformations

    N/A
    0 Ratings
    9.2
    92%
    40 Ratings

    Complex transformations

    N/A
    0 Ratings
    7.6
    76%
    39 Ratings

    Data Modeling

    Apache Spark

    Feature Set Not Supported
    N/A
    7.2

    SSIS

    72%
    SQL Server Integration Services ranks higher in 6/6 features

    Data model creation

    N/A
    0 Ratings
    8.2
    82%
    17 Ratings

    Metadata management

    N/A
    0 Ratings
    8.0
    80%
    22 Ratings

    Business rules and workflow

    N/A
    0 Ratings
    6.5
    65%
    33 Ratings

    Collaboration

    N/A
    0 Ratings
    5.6
    56%
    28 Ratings

    Testing and debugging

    N/A
    0 Ratings
    7.5
    75%
    38 Ratings

    feature 1

    N/A
    0 Ratings
    7.0
    70%
    1 Rating

    Data Governance

    Apache Spark

    Feature Set Not Supported
    N/A
    6.5

    SSIS

    65%
    SQL Server Integration Services ranks higher in 2/2 features

    Integration with data quality tools

    N/A
    0 Ratings
    8.7
    87%
    28 Ratings

    Integration with MDM tools

    N/A
    0 Ratings
    4.4
    44%
    26 Ratings

    Attribute Ratings

    • Apache Spark is rated higher in 3 areas: Likelihood to Recommend, Usability, Support Rating
    • Apache Spark and SQL Server Integration Services are tied in 1 area: Likelihood to Renew

    Likelihood to Recommend

    9.2

    Apache Spark

    92%
    22 Ratings
    8.2

    SSIS

    82%
    40 Ratings

    Likelihood to Renew

    10.0

    Apache Spark

    100%
    1 Rating
    10.0

    SSIS

    100%
    3 Ratings

    Usability

    9.4

    Apache Spark

    94%
    2 Ratings
    9.3

    SSIS

    93%
    8 Ratings

    Performance

    Apache Spark

    N/A
    0 Ratings
    8.8

    SSIS

    88%
    12 Ratings

    Support Rating

    8.7

    Apache Spark

    87%
    6 Ratings
    8.2

    SSIS

    82%
    14 Ratings

    Implementation Rating

    Apache Spark

    N/A
    0 Ratings
    10.0

    SSIS

    100%
    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.
    Thomas Young | TrustRadius Reviewer

    SSIS

    Well suited: all data extraction from file (spreadsheet-like) and RDBMS data sources, mix up them into one integrated meta-data source for future processing.Less appropriate: big key-value data storages processed slowly, and hard to make data mining through uniting non-RDBMS and RDBMS data sources naive way. The data from non-SQL databases should be prepared accordingly to be represented in a table-like way if possible.
    Vladimir Salnikov | TrustRadius Reviewer

    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
    Nitin Pasumarthy | TrustRadius Reviewer

    SSIS

    • Ease of use - can be used with no prior experience in a relatively short amount of time.
    • Flexibility - provides multiple means of accomplishing tasks to be able to support virtually any scenario.
    • Performance - performs well with default configurations but allows the user to choose a multitude of options that can enhance performance.
    • Resilient - supports the configuration of error handling to prevent and identify breakages.
    • Complete suite of configurable tools.
    Anonymous | TrustRadius Reviewer

    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
    Anson Abraham | TrustRadius Reviewer

    SSIS

    • SSIS has been a bit neglected by Microsoft and new features are slow in coming.
    • When importing data from flat files and Excel workbooks, changes in the data structure will cause the extracts to fail. Workarounds do exist but are not easily implemented. If your source data structure does not change or rarely changes, this negative is relatively insignificant.
    • While add-on third-party SSIS tools exist, there are only a small number of vendors actively supporting SSIS and license fees for production server use can be significant especially in highly-scaled environments.
    Anonymous | TrustRadius Reviewer

    Pricing Details

    Apache Spark

    General

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

    Starting Price

    SSIS

    General

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

    Starting Price

    Likelihood to Renew

    Apache Spark

    Apache Spark 10.0
    Based on 1 answer
    Capacity of computing data in cluster and fast speed.
    Steven Li | TrustRadius Reviewer

    SSIS

    SSIS 10.0
    Based on 3 answers
    Some features should be revised or improved, some tools (using it with Visual Studio) of the toolbox should be less schematic and somewhat more flexible. Using for example, the CSV data import is still very old-fashioned and if the data format changes it requires a bit of manual labor to accept the new data structure
    Luca Campanelli | TrustRadius Reviewer

    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.
    Anonymous | TrustRadius Reviewer

    SSIS

    SSIS 9.3
    Based on 8 answers
    SQL Server Integration Services is a relatively nice tool but is simply not the ETL for a global, large-scale organization. With developing requirements such as NoSQL data, cloud-based tools, and extraordinarily large databases, SSIS is no longer our tool of choice.
    Anonymous | TrustRadius Reviewer

    Performance

    Apache Spark

    No score
    No answers yet
    No answers on this topic

    SSIS

    SSIS 8.8
    Based on 12 answers
    Raw performance is great. At times, depending on the machine you are using for development, the IDE can have issues. Deploying projects is very easy and the tool set they give you to monitor jobs out of the box is decent. If you do very much with it you will have to write into your projects performance tracking though.
    Steven Gockley, MBA, MCSA | TrustRadius Reviewer

    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.
    Yogesh Mhasde | TrustRadius Reviewer

    SSIS

    SSIS 8.2
    Based on 14 answers
    The support, when necessary, is excellent. But beyond that, it is very rarely necessary because the user community is so large, vibrant and knowledgable, a simple Google query or forum question can answer almost everything you want to know. You can also get prewritten script tasks with a variety of functionality that saves a lot of time.
    Chris Morgan | TrustRadius Reviewer

    Implementation Rating

    Apache Spark

    No score
    No answers yet
    No answers on this topic

    SSIS

    SSIS 10.0
    Based on 2 answers
    The implementation may be different in each case, it is important to properly analyze all the existing infrastructure to understand the kind of work needed, the type of software used and the compatibility between these, the features that you want to exploit, to understand what is possible and which ones require integration with third-party tools
    Luca Campanelli | TrustRadius Reviewer

    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.
    Anonymous | TrustRadius Reviewer

    SSIS

    Look for where you are going to load the data and from where are you extracting it. A lot of those who sell you the DB already have tools for ETL. I have heard good things at an enterprise level from great colleagues about Informatica, but honestly, I prefer SSIS.Although I did like TIBCO Jaspersoft and it can be mixed with TIBCO Spotfire for data analysis. If your ERP is SAP, then you must keep in mind using SAP BusinessObjects. As for free tools, and if you have a great and constant team of scripting (Perl, Python) engineers, then you can think about going open source.
    Jose Pla | TrustRadius Reviewer

    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
    Surendranatha Reddy Chappidi | TrustRadius Reviewer

    SSIS

    • I use SSIS to automate tasks that I'm repeatedly asked to do. "Hey, can you go into the system and close any open orders that we've fully filled?" Sure....then I schedule a package to do that for me every hour so I'm never asked again. It saves me time, which gives value to the company.
    • It removes the risk of human error. When people build files and send them, there's the risk that it doesn't happen the same way every time or gets forgotten. With SSIS, you spend some up front time building a process, but then you deploy it and forget it (unless it emails you that there was an error. You are putting error handling in your ETL, right?). Very repeatable and consistent business solution.
    Greg Goss | TrustRadius Reviewer

    Add comparison