Snowflake vs. Informatica: Data Management Comparison

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Both Snowflake and Informatica are data management platforms that are well regarded in the industry.

These data management applications are in heavy demand as organizations seek to harness the vast troves of data at their disposal. Without these data analytics tools, analysts and data scientists would struggle with problems such as data dispersal throughout the enterprise in multiple repositories, lack of data integration, and a variety of other data management challenges.

As both Snowflake and Informatica are leading data management platforms, users sometimes must choose between them. There are arguments for and against each.

Which of these well-respected platforms is best? Both provide the volume, speed, and quality demanded by the data analytics applications they typically support. There are as many similarities as there are differences. Yet they each have different orientations. Therefore, selection often boils down to platform preference and suitability for the organization’s data strategy.

Also see: Best Data Analytics Tools 

Snowflake vs. Informatica: Key Features

The Informatica Intelligent Data Management Cloud (IDMC) helps businesses handle dispersed and fragmented data on any platform, any cloud, on multi-cloud and multi-hybrid. It is a cloud-native, AI-powered and offers over 200 data services and it processes over 17 trillion transactions per month.

Organizations can use Informatica to share, deliver, and democratize data across lines of business and other enterprises. Data catalog scans metadata to discover and understand enterprise data. Data integration accesses and integrates data at scale using serverless computing.

Informatica’s API & App Integration connects applications and automates business processes. MDM & 360 applications provide 360 views of business data. Informatica IDMC is powered by an AI and ML engine called Claire. It can be used to discover and understand all data within and outside the enterprise, access and ingest all types of data, and curate and prepare data in a self-service fashion.

Most recently, the company announced a new suite of cloud data management services for AWS which is aimed at providing broader data management to departmental users, developers, data scientists, and data engineers across all skill levels. Informatica Data Loader on AWS is embedded directly into the Amazon Redshift console to enable movement from data ingestion to insights in minutes.

Informatica Data Marketplace supports AWS Data Exchange as part of the self-service data marketplace. Informatica INFACore supports Amazon SageMaker Studio to simplify management of complex data pipelines for building and deploying ML models.

Snowflake, in contrast, is a relational database management system and analytics data warehouse for structured and semi-structured data. Offered through the Software-as-a-Service (SaaS) model, it uses an SQL database engine to manage how information is stored in the database, and process queries against virtual warehouses within the overall warehouse, with each one of its cluster nodes independent of others and not sharing compute resources.

Sitting on top of that are cloud services for authentication, infrastructure management, queries, access controls, and so on. The Snowflake Elastic Data Warehouse enables users to analyze and store data utilizing Amazon S3 or Azure resources.

Overall, Snowflake should be regarded more as a data lake or data warehouse that facilitates analytics than a full-featured analytics application. As such, it is particularly good at managing, processing, aggregating, and sharing large amounts of data across a business. Good archiving features are also present.

Late in 2022, Snowflake released some platform updates. These included performance advancements across its single elastic engine to make it faster while improving economics for users. In addition, Snowflake’s Snowgrid technology enables customers to operate at global scale with enhancements across cross-cloud collaboration, cross-cloud data governance, and cross-cloud business continuity.

Overall, there is little to choose between the two. No clear winner here.

Snowflake vs. Informatica: Support and Ease of Use

Informatica Data Loader is a high-speed, no-cost, simple tool requiring no setup for data-savvy departmental users looking for frictionless, high-volume data loading that generates insights from data in minutes. The new functionality offers customers the ability to launch Informatica Data Loader from the Amazon Redshift console in a few clicks, easily ingesting data from AWS, on-premise, legacy systems, third-party applications, and other sources. Using a guided interface, customers can load and combine data in their data warehouse for insights into their business without having to build a custom solution. It scores well on ease of use.

The Snowflake data warehouse is said by users to be user-friendly with an intuitive SQL interface that makes it easy to get it set up and running. It automates data vacuuming, compression, diagnosis, and other features. There is no need to copy data during scale up operations with Snowflake. For third-party data sharing and access to conduct analysis, Snowflake makes the entire process much easier.

Snowflake supports structured and semi-structured data. Users also report that its ability to handle many columns is strong. But some same the documentation is weak and that a lack of out-of-the box analytics holds it back. Gartner Peer Reviews give it a good score on ease of deployment and administration.

Informatica wins narrowly in this category. 

Also see: Data Analytics Trends 

Snowflake vs. Informatica: Security

Informatica prides itself in baking in security and trust as central design principles. It does this to ensure the highest level of security and a consistent level of data quality, end-to-end data governance and data privacy across the enterprise. For enterprise users, it reduces regulatory risk by ensuring the accuracy and protection of sensitive data.

Snowflake boasts always-on encryption, along with network isolation, secure access-based requests, and other robust security features. Its security features are tiered with each higher tier costing more. That means you don’t end up paying for security features you don’t need or want.

No clear winner in this category.

Snowflake vs Informatica: Integration

Informatica is one of the few vendors that packages customer first-party data sets and third-party data sets from AWS Data Exchange to be leveraged via Informatica’s Data Marketplace. This assists in discovery, packaging, and delivery of third-party data from AWS Data Exchange. It further enables enterprise data consumers to use internal and third-party data hosted on AWS Data Exchange, which has more than 3,500 data products and more than 300 data providers. This helps to meet users via a self-service model. It can be run in multi-cloud, multi-hybrid, and on-premises infrastructures.

Snowflake is on the AWS Marketplace, which helps integrate it within that ecosystem. Some users say that with certain analytics applications, it can be challenging to integrate Snowflake. But in other analytics use cases, Snowflake is wonderfully integrated. Tableau, Apache Spark, IBM Cognos, and Qlik are all fully integrated. Those using these tools will find analysis easy to accomplish. Regardless, Gartner Peer Reviews rates Snowflake highly for integration and deployment.

Integration: Informatica narrowly wins.

Snowflake vs. Informatica: Pricing

Snowflake costs about $40 a month. But rate of usage will vary tremendously depending on the workload. Some users say large data sets cost more on Snowflake due to the way it offers separate pricing for compute and storage.

On-demand pricing is a feature of Snowflake. It also provides concurrency scaling automatically with all editions at no extra cost. Pricing, though, can be complex with four different editions from basic up, and prices rise as you move up the tiers. You can either pay for capacity upfront or choose a pay as you go model for storage.

The Informatica Processing Unit (IPU) pricing system is built around buying only the capacity you need for different services such as data integration, mass ingestion, data quality, API and App integration, and Catalog and Governance. But rates are hard to find.

Thus, differences between them make it difficult to do a full comparison. Users are advised to assess the resources they expect to need to support their forecast data volume, amount of processing, and their analysis requirements.

This is a close one as it varies from use case to use case, but Snowflake wins by a hair on pricing.

Also see: Data Mining Techniques 

Snowflake vs. Informatica: Conclusion

Snowflake and Informatica are excellent data management tools for analysis purposes. Each has its pros and cons. It all comes down to usage patterns, data volumes, workloads, and data strategies.

Both are good choices when data management, integration, and sharing are the biggest needs. Those wanting to centralize data across multiple data repositories and with large amounts of data will find both invaluable. Top-notch analytics can be added on via other platforms.

Some say Snowflake is better when you are starting small and gradually scaling up.

But these are generalities and won’t always pan out. Each business needs to research how costs will work out for them. The latest Gartner Magic Quadrant (MQ) for Data Integration Tools has Informatica scoring the highest among all vendors. Gartner did not consider Snowflake as part of that MQ. That tends to indicate that where data integration needs are highest, Informatica is the obvious choice. But for broader cloud data management needs, Snowflake may be a better choice.

Also see: What is Data Visualization