IBM watsonx.data vs. Snowflake

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM watsonx.data
Score 8.8 out of 10
N/A
Watsonx.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
Snowflake
Score 8.7 out of 10
N/A
The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.N/A
Pricing
IBM watsonx.dataSnowflake
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM watsonx.dataSnowflake
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM watsonx.dataSnowflake
Considered Both Products
IBM watsonx.data
Chose IBM watsonx.data
It is better then competitors but not always, it depends on how we use in our environment. IBM watsonx.data has strong data governance.
Chose IBM watsonx.data
Snowflake is a more mature, simpler to use product but watsonx.data has a more open architecture and it better for hybrid cloud environments. In addition, watsonx.data is part of an entire watsonx platform that offers many advantages over is closest competitors. The single …
Chose IBM watsonx.data
Already using the watsonx.orchestrate, so it's was easier to incorporate this into existing infrastructure.
Chose IBM watsonx.data
IBM watsonx.ai and IBM watsonx.governance
Chose IBM watsonx.data
The three pair nicely together to create my own RAG solution in a controlled manner.
Chose IBM watsonx.data
We chose IBM watsonx.data for our organization because IBM watsonx.data has Open-source support
Chose IBM watsonx.data
IBM watsonx.data stacks up against Snowflake very well. It come in at a less expensive price. Also, you can run IBM watsonx.data on any cloud. or on prem.. Much more flexible.
Chose IBM watsonx.data
with iceberg open table format and presto engine the performance and flexibility increased and also with watsonx.ai with GENAI capability which other tools lag as of now.
Chose IBM watsonx.data
We use IBM watsonx.data as a unified data platform to integrate and govern data across systems, eliminating silos and improving data quality. Its open lakehouse architecture enables faster, trusted access to data for AI, analytics, and reporting, forming the foundation for …
Chose IBM watsonx.data
Salesforce Genie and Snowflake
Chose IBM watsonx.data
Oracle really cost effective solution, where it has the support of community, with rich integration of all wide range of oracle products.
Amazon sageMaker is another cost effective solution, where is tightly coupled with AWS platform, in terms of performance it copes up really …
Chose IBM watsonx.data
IBM watsonx.data integrates well with other IBM services used in our deployment and provides enterprise grade security which is critical for our regulated business
Chose IBM watsonx.data
AstraDB was giving me vector database solutions, Retrieval Augmented Generation features and even Agentic workflows that IBM watsonx.data does not have currently. But the volume of data I've coming everyday and has to deal with everyday, can do anomaly detection just in plain …
Chose IBM watsonx.data
Pinecone and IBM watsonx.data (Milvus in our case) both work great as a full-managed cloud-based vector database.
We selected IBM watsonx.data because it integrates well with watson.ai and is a little more beginner friendly than pinecone, but I think both are great anyway.
Chose IBM watsonx.data
IBM watsonx.data helps in reducing data warehousing costs. IBM AIOps Insights focuses mainly on incident management, while IBM watsonx.data provides a flexible data store.
Chose IBM watsonx.data
May be I cannot say why I choose, business preferred to use IBM watsonx.data which is good for me as well to learn. I cannot compare this tool with others because it has unique feature which alteryx or Amazon or Azure dont have. So this tool is going good for us.
Chose IBM watsonx.data
I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating …
Chose IBM watsonx.data
DataStax Enterprise offered best-in-class write performance and scalability. The customer support team was very helpful in the adoption of new technology.
Chose IBM watsonx.data
DataStax has an amazing community built around it and is also Cassandra is an open-source technology. The customer support is quite good compared to other vendors. Though you initially need to spend some hefty amount on infrastructure, in the long run, it makes up for it. We …
Chose IBM watsonx.data
We chose datastax because we need a system always available and capable of ingesting a large amount of data per second, even if eventually consistent and with multi data center sync native support.

We considered Cloudera as an alternative using Kafka as the ingestion layer but …
Chose IBM watsonx.data
Amazon DynamoDB and Datastax Cassandra are similar on masterless architecture and principles, DynamoDB is managed and needs cost analysis. If you need to have better control, Datastax is better.

I also did a prototype with Google Spanner in one of the recent innovation days, it …
Snowflake
Chose Snowflake
We use these tools for applications they are better suited for vs a Snowflake. For e.g. MS Fabric has powerful agentic AI capabilities; Redshift is our go to choice for the TMT vertical within the organization and Databricks is the default choice for AI/ML applications.
Chose Snowflake
Snowflake provides various features, such as integration with Python using Snowpark. The reporting feature that caters to your small reporting needs is Snowsight. The Snowflake data marketplace is where you can get multiple data for free and even some of the data which you can …
Chose Snowflake
These are comparable products that can make sense depending on the specific needs of your organization. All are certainly serviceable and have varying pros and cons. Snowflake seems to provide the greatest degree of flexibility and easy scalability as new data gets brought into …
Chose Snowflake
Snowflake stacks up well against many of the other players in the space. We used Teradata before and it seems to perform better.
Chose Snowflake
We needed scalability and a new way of organizing our data; Snowflake allowed us to have a clearer view of our data warehouses and schemas. Snowflake is also way superior in terms of speed and quick insights from the raw data you query, which is very valuable to us.
Chose Snowflake
Snowflake has an attractive pricing model with auto-suspend and auto-resume and pay per use. AWS Redshift requires higher administrative efforts to maintain and scale the platform whereas with Snowflake those admin tasks are not needed or automatically taken care of.
Chose Snowflake
Cloud -Native architecture, Separation of Storage and Compute provides flexibility, Scalable Compute, Cost and Data Security
Chose Snowflake
We had a MS SQL server with over 2 TB of ram & 51 processors that we were using, that could no longer handle our workload. Snowflake can handle 3 times that workload with ease and efficiency.
Chose Snowflake
Snowflake is much faster and easier to write queries and pull data. But the visualization part of Snowflake is not as good as them. Also, Snowflake only supports SQL queries but not python or other languages. So basically Snowflake is the expert in its field but not suitable …
Chose Snowflake
We particularly liked Snowflake's security model as well as its unique storage (whereby everything is essentially a pointer to immutable micro-partitions, which is the key behind its zero-copy cloning, its secure sharing, its time travel, etc.). and also how it separates …
Chose Snowflake
While Snowflake is more open to cloud eco system, SAP integrated well with SAP eco system products like SAP ECC or SAP S/4. So for people who have invested heavily in SAP eco system including SAP ECC or S/4, it makes sense to go with SAP DWC which is also evolving very rapidly. …
Chose Snowflake
In my opinion, the other tools have similar and some different features; however, when I ran proof of technologies between Synapse and Snowflake. Snowflake did things better or just had functionality that the other tools did not. One that stuck out at the time was scale up …
Chose Snowflake
Each of the other solutions were cloud vendor specific, Snowflake can ride on either Amazon Web Services, Microsoft Azure, or Google Cloud. The fact that they are ANSI-sql compliant and have an effective means of offloading data makes them portable and easy to sell to teams …
Chose Snowflake
Azure and Snowflake compared very similarly, but Snowflake provided more options to integrate and connect with tools/companies that were not partners. It seemed to be a more flexible environment. The barrier for entry on Oracle and Google we just too complicated. In particular, …
Chose Snowflake
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system …
Chose Snowflake
Snowflake has won the match because it is giving an excellent performance with its efficient features and reliable results. This is a totally secure program for our precious and important data.
Chose Snowflake
Our initial data warehousing solution was Treasure Data. We had issues with the costly pricing model, which would be exhorbitant if we want to hold our data in memory and query using Presto. As a result, some heavy lifting was done in Hive (managed by Treasure Data); …
Chose Snowflake
Snowflake beats these other products in every category it was rated against
Chose Snowflake
In my experience running the data management practice at InterWorks, we believe that cloud data warehouse products will eventually serve the majority of data warehousing use cases and power data analytics at most companies. Of this cohort, we believe that Snowflake is the best …
Chose Snowflake
Redshift compute and storage can be scaled up/down together (though they added some features recently, they don't quite add up). I haven't tried Avalanche or Firebolt but would love to in the near future, due to their pedigree or revolutionary billing methods.
Chose Snowflake
- Cost was the main aspect on the decision.
- Performance was in par or better compared to other tools in the market.
- Snowflake in my opinion stacks better than other tools I have used in the past.
Chose Snowflake
Accommodates future data types such as JSON and XML. Scalability is another advantage. Pay per use is beneficial for organizations like yours. Direct connectors with AWS help us to go with it. No limit on user creation and clone data not eating up extra disk space are a few …
Chose Snowflake
Since we switch from amazon redshift to Snowflake, we found Snowflake is much better than redshift in many ways, including the data integrate and data pull. However, comparing directly pull data from amazon s3, Snowflake is quite slow in terms of data pull speed and the more …
Chose Snowflake
Compared to Amazon Redshift, Snowflake is slightly easier and faster to achieve ROI but based on the user's perspective, the two tools have very little difference since both are leveraging SQL to pull data from AWS S3. Snowflake is also working with Microsoft Azure but it is …
Chose Snowflake
Our issue with Redshift was that it was very expensive. On top of that, queries were still slow and if we used more of Redshift's memory, then it would have cost even more. Snowflake is not cheap, but less costly for us. Plus, the performance was much better. Also, we got to …
Best Alternatives
IBM watsonx.dataSnowflake
Small Businesses

No answers on this topic

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Score 8.7 out of 10
Medium-sized Companies
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Score 8.7 out of 10
Google BigQuery
Google BigQuery
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Enterprises
Snowflake
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Score 8.7 out of 10
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User Ratings
IBM watsonx.dataSnowflake
Likelihood to Recommend
8.8
(0 ratings)
8.8
(0 ratings)
Likelihood to Renew
7.3
(0 ratings)
7.0
(0 ratings)
Usability
7.9
(0 ratings)
8.9
(0 ratings)
Availability
8.2
(0 ratings)
-
(0 ratings)
Performance
8.2
(0 ratings)
-
(0 ratings)
Support Rating
9.1
(0 ratings)
9.9
(0 ratings)
Online Training
8.2
(0 ratings)
-
(0 ratings)
Implementation Rating
8.2
(0 ratings)
-
(0 ratings)
Configurability
8.2
(0 ratings)
-
(0 ratings)
Ease of integration
7.3
(0 ratings)
-
(0 ratings)
Product Scalability
7.3
(0 ratings)
-
(0 ratings)
Vendor post-sale
8.2
(0 ratings)
-
(0 ratings)
Vendor pre-sale
8.2
(0 ratings)
-
(0 ratings)
User Testimonials
IBM watsonx.dataSnowflake
Likelihood to Recommend
Datastax Cassandra is a Java based linearly scalable NoSQL database, best-in-class tunable performance, fault tolerant, distributed, masterless, time series database and has easy-to-use administration and monitoring functionality with opscenter. Configured correctly there is no downtime and no data loss. The documentation is exhaustive, and the community is agile and supportive, and Datastax provides good support. For all these reasons, Datastax Cassandra has become a NoSQL technology of choice for many platforms. However it has some time investment on infrastructure and regular operational tasks, and if you do not have bandwidth for it, a managed NoSQL solution like DynamoDB might be more appropriate. Also if you have search needs on Cassandra and do not have corresponding Spark/Solr setup, Datastax Cassandra might not be ideal for you.
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If you need a quick query, snowflake is the way to go. It's super simple and scalable; we were struggling before with Azure, and with Snowflake, everything runs smoothly, and we have more control over our schemas and warehouses. Snowflake, in my opinion, is the next step when you want to scale your business and manage data. If your company is still small, there may be cheaper options.
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Pros
  • It doesn't just store data but unlocks potential. I am able to analyse a vast amount of information, identify trends, and predict future outcomes.
  • It not only gives me high quality but accessible data as well. It handles missing values, outliers and feature engineering with case.
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  • Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
  • Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
  • Snowflake manages concurrency better in our trials than other premium competitors
  • Snowflake has little to no setup and ramp up time
  • Snowflake offers online training for various employee types
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Cons
  • Integration complexity with Security Tools while watsonx.Data is well-suited for native tools, but integration with third-party security tools requires custom connectors or manual ETL pipelines. which leads to an increase in setup time.
  • User interface and query time can be improved.
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  • Add constraints for views and not just for tables
  • Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
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Likelihood to Renew
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.
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SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
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Usability
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.
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The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
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Reliability and Availability
good recovery features
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No answers on this topic
Performance
scalable product
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No answers on this topic
Support Rating
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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We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
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Online Training
easy to follow documentation, support is there when needed
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No answers on this topic
Implementation Rating
use saas service
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No answers on this topic
Alternatives Considered
I believe DataStax Enterprise is the best in class. There are some things that are different with the schema-less systems but I found DataStax Enterprise easiest to implement while evaluating. The replication is on par or better than others in practice. We are evaluating Astra in our test environment and that has additional benefits we are looking forward to using.
Read full review
Snowflake provides various features, such as integration with Python using Snowpark. The reporting feature that caters to your small reporting needs is Snowsight. The Snowflake data marketplace is where you can get multiple data for free and even some of the data which you can buy according to your needs. And the integration options with various tools like Sigma are add-ons.
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Scalability
cognos integration works great
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No answers on this topic
Return on Investment
  • 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
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  • With separate compute and storage feature, the queries get executed quickly and it improves our overall productivity.
  • Earlier we were using a different product for analytical purposes, but with Snowflake's in-built analytical feature we are now able to save money.
  • Snowflake is cost efficient, features like auto suspend for compute resources helped to control the costs.
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ScreenShots

Snowflake Screenshots

Screenshot of Snowflake Installation