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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM DataStage

    Score8 out of 10
    N/AIBM® DataStage® is a data integration tool that helps users to design, develop and run jobs that move and transform data. At its core, the DataStage tool supports extract, transform and load (ETL) and extract, load and transform (ELT) patterns. A basic version of the software is available for on-premises deployment, and the cloud-based DataStage for IBM Cloud Pak® for Data offers automated integration capabilities in a hybrid or multicloud environment.N/A

    MongoDB

    Score8.8 out of 10
    N/AMongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.

    $0.10

    million reads

    Pricing
    IBM DataStageMongoDB
    Editions & Modules
    No answers on this topic
    Shared
    $0
    per month
    Serverless
    $0.10million reads
    million reads
    Dedicated
    $57
    per month
    Offerings
    Pricing Offerings
    IBM DataStageMongoDB
    Free Trial
    YesYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details—Fully managed, global cloud database on AWS, Azure, and GCP
    More Pricing Information
    Community Pulse
    IBM DataStageMongoDB
    Considered Both Products
    IBM
    No answer on this topic
    MongoDB
    Chose MongoDB
    This tool is only capable of reading real-time data very smoothly. The transition was also pretty easy and quick. Syntax is also very easy and comfortable to learn and use.

    The main reason for selecting is that it works very fast under the Intellijet module environment and we …
    Incentivized
    Key User Insights
    Would buy again
    89%
    Would buy again
    8 Answers
    100%
    Would buy again
    12 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    5 Answers
    100%
    Delivers good value for the price
    12 Answers
    Happy with the feature set
    89%
    Happy with the feature set
    8 Answers
    100%
    Happy with the feature set
    12 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    7 Answers
    100%
    Lived up to sales and marketing promises
    9 Answers
    Implementation went as expected
    88%
    Implementation went as expected
    7 Answers
    100%
    Implementation went as expected
    12 Answers
    Features
    IBM DataStageMongoDB
    Data Source Connection
    Comparison of Data Source Connection features of IBM DataStage and MongoDB
    Feature
    IBM DataStage
    7.7
    11 Ratings
    8% below category average
    MongoDB
    -
    Ratings
    Connect to traditional data sources7.911 Ratings00 Ratings
    Connecto to Big Data and NoSQL7.610 Ratings00 Ratings
    Data Transformations
    Comparison of Data Transformations features of IBM DataStage and MongoDB
    Feature
    IBM DataStage
    7.6
    11 Ratings
    7% below category average
    MongoDB
    -
    Ratings
    Simple transformations8.011 Ratings00 Ratings
    Complex transformations7.311 Ratings00 Ratings
    Data Modeling
    Comparison of Data Modeling features of IBM DataStage and MongoDB
    Feature
    IBM DataStage
    7.2
    11 Ratings
    10% below category average
    MongoDB
    -
    Ratings
    Data model creation7.18 Ratings00 Ratings
    Metadata management5.010 Ratings00 Ratings
    Business rules and workflow7.410 Ratings00 Ratings
    Collaboration7.411 Ratings00 Ratings
    Testing and debugging6.711 Ratings00 Ratings
    Data Governance
    Comparison of Data Governance features of IBM DataStage and MongoDB
    Feature
    IBM DataStage
    5.3
    10 Ratings
    42% below category average
    MongoDB
    -
    Ratings
    Integration with data quality tools5.310 Ratings00 Ratings
    Integration with MDM tools5.310 Ratings00 Ratings
    NoSQL Databases
    Comparison of NoSQL Databases features of IBM DataStage and MongoDB
    Feature
    IBM DataStage
    -
    Ratings
    MongoDB
    10.0
    39 Ratings
    16% above category average
    Performance00 Ratings10.039 Ratings
    Availability00 Ratings10.039 Ratings
    Concurrency00 Ratings10.039 Ratings
    Security00 Ratings10.039 Ratings
    Scalability00 Ratings10.039 Ratings
    Data model flexibility00 Ratings10.039 Ratings
    Deployment model flexibility00 Ratings10.038 Ratings
    Best Alternatives
    IBM DataStageMongoDB
    Small Businesses
    Skyvia
    Score10 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Medium-sized Companies
    IBM InfoSphere Information Server
    Score10 out of 10
    IBM Cloudant
    Score7.4 out of 10
    Enterprises
    SolarWinds Task Factory
    Score8.3 out of 10
    IBM Cloudant
    Score7.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM DataStageMongoDB
    Likelihood to Recommend
    5.9
    (11 ratings)
    10.0
    (79 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    10.0
    (67 ratings)
    Usability
    8.0
    (4 ratings)
    10.0
    (15 ratings)
    Availability
    -
    (0 ratings)
    9.0
    (1 ratings)
    Performance
    9.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    9.6
    (3 ratings)
    9.6
    (13 ratings)
    Implementation Rating
    -
    (0 ratings)
    8.4
    (2 ratings)
    User Testimonials
    IBM DataStageMongoDB
    Likelihood to Recommend
    IBM
    DataStage is somewhat outdated for an ETL. I guess that's what makes it a bit lagged behind its competitors. It can be used for data processing, sure, but its performance seems to be lagging behind or quite slow given the server it is running from. I won’t depend on this application if it's handling a lot of mission-critical banking and business data.
    Read full review
    MongoDB
    If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
    Incentivized
    Read full review
    Pros
    IBM
    • Connect to multiple types of data-sources including Oracle, Teradata, Snowflake, SQl Server.
    • Powerful tool to load large volumes of data.
    • Transformation stages allow us to reduce the amount of code needed to create ETL scripts.
    • Allow us to synchronize and refresh data as much as needed.
    Incentivized
    Read full review
    MongoDB
    • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
    • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
    • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
    Incentivized
    Read full review
    Cons
    IBM
    • Technical support is a key area IBM should improve for this product. Sometimes our case is assigned to a support engineer and he has no idea of the product or services.
    • Provide custom reports for datastage jobs and performance such as job history reports, warning messages or error messages.
    • Make it fully compatible with Oracle and users can direct use of Oracle ODBC drivers instead of Data Direct driver. Same for SQL server.
    Incentivized
    Read full review
    MongoDB
    • An aggregate pipeline can be a bit overwhelming as a newcomer.
    • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
    • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    No answers on this topic
    MongoDB
    I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
    Incentivized
    Read full review
    Usability
    IBM
    Because it is robust, and it is being continuously improved. DS is one of the most used and recognized tools in the market. Large companies have implemented it in the first instance to develop their DW, but finding the advantages it has, they could use it for other types of projects such as migrations, application feeding, etc.
    Incentivized
    Read full review
    MongoDB
    NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
    Incentivized
    Read full review
    Performance
    IBM
    It could load thousands of records in seconds. But in the Parallel version, you need to understand how to particionate the data. If you use the algorithms erroneously, or the functionalities that it gives for the parsing of data, the performance can fall drastically, even with few records. It is necessary to have people with experience to be able to determine which algorithm to use and understand why.
    Incentivized
    Read full review
    MongoDB
    No answers on this topic
    Support Rating
    IBM
    IBM offers different levels of support but in my experience being and IBM shop helps to get direct support from more knowledgeable technicians from IBM. Not sure on the cost of having this kind of support, but I know there's also general support and community blogs and websites on the Internet make it easy to troubleshoot issues whenever there's need for that.
    Incentivized
    Read full review
    MongoDB
    Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
    Incentivized
    Read full review
    Implementation Rating
    IBM
    No answers on this topic
    MongoDB
    While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
    Incentivized
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    Alternatives Considered
    IBM
    With effective capabilities and easy to manipulate the features and easy to produce accurate data analytics and the Cloud services Automation, this IBM platform is more reliable and easy to document management. The features on this platform are equipped with excellent big data management and easy to provide accurate data analytics.
    Incentivized
    Read full review
    MongoDB
    We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
    Read full review
    Return on Investment
    IBM
    • It’s hard to say at this point, it delivers, but not quite as I expected. It takes a lot of resources to manage and sort this out (manpower, financial).
    • Definitely, I don’t have the exact numbers, but given the data it processes, it is A LOT. So props to the developer of this application.
    • Again, based on my experience, I’d choose other ETL apps if there is one that's more user-friendly.
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    MongoDB
    • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
    • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
    Read full review
    ScreenShots

    MongoDB Screenshots

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