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IBM watsonx.data vs. Teradata Autonomous Knowledge Platform

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM watsonx.data

    Score8.4 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

    Teradata Autonomous Knowledge Platform

    Score8 out of 10
    N/ATeradata Vantage is presented as a modern analytics cloud platform that unifies everything—data lakes, data warehouses, analytics, and new data sources and types. Supports hybrid multi-cloud environments and priced for flexibility, Vantage delivers unlimited intelligence to build the future of business. Users can deploy Vantage on public clouds (such as AWS, Azure, and GCP), hybrid multi-cloud environments, on-premises with Teradata IntelliFlex, or on commodity hardware with VMware.

    $4,800

    per month

    Pricing
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Editions & Modules
    No answers on this topic
    Teradata VantageCloud Lake
    from $4800
    per month
    Teradata VantageCloud Enterprise
    from $9000
    per month
    Offerings
    Pricing Offerings
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Free Trial
    YesYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoYes
    Entry-level Setup FeeNo setup feeOptional
    Additional Details——
    More Pricing Information
    Community Pulse
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Considered Both Products
    IBM
    No answer on this topic
    Teradata
    No answer on this topic
    Key User Insights
    Would buy again
    94%
    Would buy again
    34 Answers
    94%
    Would buy again
    47 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    30 Answers
    100%
    Delivers good value for the price
    37 Answers
    Happy with the feature set
    97%
    Happy with the feature set
    35 Answers
    98%
    Happy with the feature set
    49 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    23 Answers
    100%
    Lived up to sales and marketing promises
    28 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    29 Answers
    97%
    Implementation went as expected
    37 Answers
    Best Alternatives
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Small Businesses
    No answers on this topic
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    Medium-sized Companies
    SAP Business Data Cloud
    Score8.6 out of 10
    Snowflake
    Score8.7 out of 10
    Enterprises
    SAP Business Data Cloud
    Score8.6 out of 10
    Snowflake
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Likelihood to Recommend
    8.2
    (34 ratings)
    9.4
    (62 ratings)
    Likelihood to Renew
    7.3
    (4 ratings)
    8.2
    (6 ratings)
    Usability
    8.0
    (10 ratings)
    9.0
    (30 ratings)
    Availability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Performance
    8.2
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    9.1
    (4 ratings)
    7.3
    (2 ratings)
    Online Training
    8.2
    (1 ratings)
    -
    (0 ratings)
    Implementation Rating
    8.2
    (1 ratings)
    6.4
    (1 ratings)
    Configurability
    8.2
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    7.3
    (1 ratings)
    -
    (0 ratings)
    Product Scalability
    7.3
    (1 ratings)
    -
    (0 ratings)
    Vendor post-sale
    8.2
    (1 ratings)
    -
    (0 ratings)
    Vendor pre-sale
    8.2
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    IBM watsonx.dataTeradata Autonomous Knowledge Platform
    Likelihood to Recommend
    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.
    Read full review
    Teradata
    Teradata Vantage is well suited for large scale ETL pipelines like the ones we developed for anti money laundering risk matrices. It handles heavy joins, aggregations, and transformations on transactional data efficiently. We generate alert variables, adjust for inflation, and monitor establishments monthly with it, all integrated with Python and Control-M for a centralised automation across the company. For less appropriate, I would say that heavy resource demands might slow down experimentation for iterative work.
    Read full review
    Pros
    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
    Read full review
    Teradata
    • ETL (Extract - Transfor - Load)
    • NOS to send data from Teradata Vantage to S3 and from S3 to Teradata Vantage
    • Teradata GeoSpacial feature
    • Bulk reading and writing in huge tables
    • MPP capacity already mature
    • Temporal Capacity more mature that other solutions
    • TASM
    Incentivized
    Read full review
    Cons
    IBM
    • Interface do need some improvement to be more intuitive for analysts like me.
    • Configuring multiple data sources can require support, as it isn't easy for new users. So, it can be made easier.
    • Additional ETL features can be added, so users don't have to switch between tools.
    Incentivized
    Read full review
    Teradata
    • Teradata is an excellent option but only for a massive amount of data warehousing or analysis. If your data is not that big then it could be a misfit for your company and cost you a lot. The cost associated is quite extensive as compared to some other alternative RDBMS systems available in the market.
    • Migration of data from Teradata to some other RDBMS systems is quite painful as the transition is not that smooth and you need to follow many steps and even if one of them fails. You need to start from the beginning almost.
    • Last but not least the UI is pretty outdated and needs a revamp. Though it is simple, it needs to be presented in a much better way and more advanced options need to bee presented on the front page itself.
    Incentivized
    Read full review
    Likelihood to Renew
    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
    Read full review
    Teradata
    Teradata is a mature RDBMS system that expands its functionality towards the current cloud capabilities like object storage and flexible compute scale.
    Incentivized
    Read full review
    Usability
    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
    Read full review
    Teradata
    Teradata Vantage allows us to create a scalable infrastructure to support our strategic initiatives. The dedicated compute power ensures reliable performance with isolated workloads and dedicated resources, optimizing workflows for faster, more efficient data transfers. The compute clusters support ETL processes and OSF’s developers and data science team with the flexibility to create self-service analytics, to spin up/down at any time, driving better performance and minimizing costs.
    Read full review
    Reliability and Availability
    IBM
    good recovery features
    Incentivized
    Read full review
    Teradata
    No answers on this topic
    Performance
    IBM
    scalable product
    Incentivized
    Read full review
    Teradata
    No answers on this topic
    Support Rating
    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.
    Read full review
    Teradata
    We have meetings at the beginning with the technical team to explain our requirements to them and they were really putting in a lot of effort to come up with a solution which will address all our needs. They implemented the software and also trained a few of our resources on the same too. We can get in touch with them now as well whenever we run into a roadblock but it's very less now.
    Incentivized
    Read full review
    Online Training
    IBM
    easy to follow documentation, support is there when needed
    Incentivized
    Read full review
    Teradata
    No answers on this topic
    Implementation Rating
    IBM
    use saas service
    Incentivized
    Read full review
    Teradata
    No answers on this topic
    Alternatives Considered
    IBM
    Claude is better for troubleshooting actual OPS/REXX but that's not an IBM product so I understand why IBM watsonx.data isn't great for that, but if IBM watsonx.data did help with code then it would be the only product that I use.
    Incentivized
    Read full review
    Teradata
    Teradata is way ahead of its competitor because of its unique features of ensuring data privacy and data never gets corrupted even in worst case scenario. In most cases, the data corruption is a major issue if left unused and it leads to important data being wiped off which in ideal case should be stored for 3 years
    Incentivized
    Read full review
    Scalability
    IBM
    cognos integration works great
    Incentivized
    Read full review
    Teradata
    No answers on this topic
    Return on Investment
    IBM
    • for one automation project, we managed to cut cloud storage costs by a third through IBM watsonx.data's lakehouse optimization
    • data integration projects have had a 20 % reduction in turnaround times. Can only imagine how that will improve with the Claude partnership
    Incentivized
    Read full review
    Teradata
    • Moving to Teradata in the Cloud-enabled a level of agility that previously didn't exist in the organization. It also enabled a level of analytic competency that was not achievable using other options on the aggressive timeline that was required. We didn't want to settle for reinventing a wheel when we had a super tuned performance capable beast readily available in Teradata. Teradata lets us focus on our business rather than spending money and effort trying to design software or database foundations features on an open source or lower performance platform.
    Incentivized
    Read full review
    ScreenShots

    Teradata Autonomous Knowledge Platform Screenshots

    Screenshot of Teradata VantageCloud Lake Console Financial GovernanceScreenshot of Teradata VantageCloud Lake Console Landing Page