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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Cassandra

    Score9 out of 10
    N/ACassandra is a no-SQL database from Apache.N/A

    IBM watsonx.data

    Score8.5 out of 10
    N/AWatsonx.data is presented as an open, hybrid and governed data store that makes it possible for enterprises to scale analytics and AI with a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.N/A
    Pricing
    CassandraIBM watsonx.data
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    CassandraIBM watsonx.data
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    CassandraIBM watsonx.data
    Considered Both Products
    Apache
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    96%
    Would buy again
    45 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    39 Answers
    Happy with the feature set
    No answers on this topic
    98%
    Happy with the feature set
    46 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    28 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    33 Answers
    Best Alternatives
    CassandraIBM watsonx.data
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    HBase
    Score7.3 out of 10
    SAP Business Data Cloud
    Score8.6 out of 10
    Enterprises
    Azure Cosmos DB
    Score9.1 out of 10
    SAP Business Data Cloud
    Score8.6 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    CassandraIBM watsonx.data
    Likelihood to Recommend
    6.0
    (16 ratings)
    8.2
    (44 ratings)
    Likelihood to Renew
    8.6
    (16 ratings)
    8.3
    (5 ratings)
    Usability
    7.0
    (1 ratings)
    8.5
    (11 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Performance
    -
    (0 ratings)
    8.2
    (1 ratings)
    Support Rating
    7.0
    (1 ratings)
    9.0
    (5 ratings)
    Online Training
    -
    (0 ratings)
    8.2
    (1 ratings)
    Implementation Rating
    7.0
    (1 ratings)
    8.2
    (1 ratings)
    Configurability
    -
    (0 ratings)
    8.2
    (1 ratings)
    Ease of integration
    -
    (0 ratings)
    8.3
    (2 ratings)
    Product Scalability
    -
    (0 ratings)
    8.3
    (2 ratings)
    Vendor post-sale
    -
    (0 ratings)
    8.2
    (1 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.2
    (1 ratings)
    User Testimonials
    CassandraIBM watsonx.data
    Likelihood to Recommend
    Apache
    Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.
    Incentivized
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    IBM
    Real-time transaction processing (both reads and writes) is where DataStax Enterprise shines. It's very fast with linear scalability should more resources be needed. Additional nodes are added very easily. DataStax Enterprise on its own (without Solr or Spark enabled) isn't well suited for long complicated reports. The data model doesn't support joining multiple tables together which is common in BI reporting.
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    Pros
    Apache
    • Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
    • Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
    • Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
    • Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.
    Incentivized
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    IBM
    • Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
    • Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
    • Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
    • Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.
    Incentivized
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    Cons
    Apache
    • Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
    • Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
    • There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.
    Incentivized
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    IBM
    • I seen the connectivity of s3 buckets on aws it is only user based authentication if it can used as role based it would be help as part of security constraint
    • Mrap connections are more flexible, But using the presto and it helps a lot
    • If the customization can be happened on the IBM watsonx.data side like connectivity and other things
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    Likelihood to Renew
    Apache
    I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.
    Incentivized
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    IBM
    As an open source technology Cassandra can be readily used with or without any commercial support. DataStax provides value-added services and features, and in the end it is up to individual situations to strike a balance between the desirability of such support/service versus the associated cost.
    Incentivized
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    Usability
    Apache
    It’s great tool but it can be complicated when it comes administration and maintenance.
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    IBM
    DataStax has a good community built around it and has amazing scalability options. Though the initial setup is a bit costly, in the long run, it makes up for it. It also has powerful monitoring tools and a clean UI.
    Incentivized
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    Reliability and Availability
    Apache
    No answers on this topic
    IBM
    good recovery features
    Incentivized
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    Performance
    Apache
    No answers on this topic
    IBM
    scalable product
    Incentivized
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    Support Rating
    Apache
    Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.
    Incentivized
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    IBM
    We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.
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    Online Training
    Apache
    No answers on this topic
    IBM
    easy to follow documentation, support is there when needed
    Incentivized
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    Implementation Rating
    Apache
    No answers on this topic
    IBM
    use saas service
    Incentivized
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    Alternatives Considered
    Apache
    We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra
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    IBM
    Cognos Analytics wont be able to have any assets without the connectivity to IBM watsonx.data lakehouse. In our environment, IBM watsonx.data serves as the primary data source for all of our assets within our Cognos Analytics environment. IBM watsonx.data also incorporates the ability to run and verify SQL schema right within the management console.
    Incentivized
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    Scalability
    Apache
    No answers on this topic
    IBM
    IBM Cognos offers exceptional scalability, making it a strong solution for organizations with growing business intelligence and reporting needs. Numerous Fortune 500 companies rely on IBM Cognos to manage complex reporting environments, support large user populations, and scale their analytics capabilities as their businesses grow.
    Incentivized
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    Return on Investment
    Apache
    • I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
    • Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.
    Incentivized
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    IBM
    • It has saved us a huge cost by offloading data-warehouse which are comparatively expensive.
    • Provides a single source of data to train AI models so we don't need to rely on multiple sources, saving infra/license costs.
    • Prevents data duplication as multiple engines can use the same data bucket for the search.
    Incentivized
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    ScreenShots