Software Alternatives, Accelerators & Startups

Databricks VS Informatica

Compare Databricks VS Informatica and see what are their differences

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Informatica logo Informatica

As the world’s leader in enterprise cloud data management, we’re prepared to help you intelligently lead—in any sector, category or niche.
  • Databricks Landing page
    Landing page //
    2023-09-14
  • Informatica Landing page
    Landing page //
    2023-03-11

Databricks features and specs

  • Unified Data Analytics Platform
    Databricks integrates various data processing and analytics tools, offering a unified environment for data engineering, machine learning, and business analytics. This integration can streamline workflows and reduce the complexity of data management.
  • Scalability
    Databricks leverages Apache Spark and other scalable technologies to handle large datasets and high computational workloads efficiently. This makes it suitable for enterprises with significant data processing needs.
  • Collaborative Environment
    The platform offers collaborative notebooks that allow data scientists, engineers, and analysts to work together in real-time. This enhances productivity and fosters better communication within teams.
  • Performance Optimization
    Databricks includes various performance optimization features such as caching, indexing, and query optimization, which can significantly speed up data processing tasks.
  • Support for Various Data Formats
    The platform supports a wide range of data formats and sources, including structured, semi-structured, and unstructured data, making it versatile and adaptable to different use cases.
  • Integration with Cloud Providers
    Databricks is designed to work seamlessly with major cloud providers like AWS, Azure, and Google Cloud, allowing users to easily integrate it into their existing cloud infrastructure.

Possible disadvantages of Databricks

  • Cost
    Databricks can be expensive, especially for large-scale deployments or high-frequency usage. It may not be the most cost-effective solution for smaller organizations or projects with limited budgets.
  • Complexity
    While powerful, Databricks can be complex to set up and manage, requiring specialized knowledge in Apache Spark and cloud infrastructure. This might lead to a steeper learning curve for new users.
  • Dependency on Cloud Providers
    Being heavily integrated with cloud providers, Databricks might face issues like vendor lock-in, where switching providers becomes difficult or costly.
  • Limited Offline Capabilities
    Databricks is primarily designed for cloud environments, which means offline or on-premise capabilities are limited, posing challenges for organizations with strict data governance policies.
  • Resource Management
    Efficiently managing and allocating resources can be challenging in Databricks, especially in large multi-user environments. Mismanagement of resources could lead to increased costs and reduced performance.

Informatica features and specs

  • Comprehensive Data Integration
    Informatica provides a wide range of data integration tools that ensure seamless data flow between various sources and destinations, catering to complex environments.
  • Scalability
    The platform is highly scalable, allowing businesses to manage and integrate large volumes of data efficiently as they grow.
  • Wide Range of Connectors
    Informatica offers a large array of pre-built connectors for databases, cloud services, and applications, simplifying the integration process.
  • Data Quality Management
    Informatica includes comprehensive data quality tools to ensure that the data being processed is accurate, complete, and consistent.
  • Strong Security Features
    Informatica provides robust security features, including data encryption, user authentication, and access control measures, to protect sensitive data.
  • User-friendly Interface
    Its intuitive user interface makes it easier for data engineers and other users to design and manage data integration workflows.
  • Extensive Support and Community
    Informatica has a strong support system and an active community that can help troubleshoot issues and share best practices.

Possible disadvantages of Informatica

  • Cost
    The licensing and maintenance costs of Informatica can be high, which may not be feasible for small and medium-sized businesses.
  • Complexity
    While powerful, the platform can be complex to set up and manage, requiring specialized skills and training.
  • Performance Issues
    In certain scenarios, users have reported performance bottlenecks, particularly when dealing with extremely large datasets or complex transformations.
  • Learning Curve
    New users may find the learning curve steep, especially if they are not familiar with data integration concepts and Informatica-specific terminologies.
  • Dependency on Other Systems
    Informatica heavily relies on other systems and databases, which means any issue with dependent systems can affect data integration workflows.
  • Support Costs
    Premium support services from Informatica can add to the overall cost, and extended support might be required for complex issues.
  • Customization Limitations
    While highly configurable, some users have found that certain customizations can be difficult or require additional scripting expertise.

Databricks videos

Introduction to Databricks

More videos:

  • Tutorial - Azure Databricks Tutorial | Data transformations at scale
  • Review - Databricks - Data Movement and Query

Informatica videos

00. Informatica Master Data Management MDM Overview

More videos:

  • Review - Modifying a Data Model in Informatica Master Data Management(MDM)

Category Popularity

0-100% (relative to Databricks and Informatica)
Data Dashboard
68 68%
32% 32
Database Tools
59 59%
41% 41
Big Data Analytics
59 59%
41% 41
Big Data
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Databricks and Informatica

Databricks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Databricks notebooks are a popular tool for developing code and presenting findings in data science and machine learning. Databricks Notebooks support real-time multilingual coauthoring, automatic versioning, and built-in data visualizations.
Source: lakefs.io
7 best Colab alternatives in 2023
Databricks is a platform built around Apache Spark, an open-source, distributed computing system. The Databricks Community Edition offers a collaborative workspace where users can create Jupyter notebooks. Although it doesn't offer free GPU resources, it's an excellent tool for distributed data processing and big data analytics.
Source: deepnote.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Databricks is a simple, fast, and collaborative analytics platform based on Apache Spark with ETL capabilities. It accelerates innovation by bringing together data science and data science businesses. It is a fully managed open-source version of Apache Spark analytics with optimized connectors to storage platforms for the fastest data access.
Source: visual-flow.com
Top Big Data Tools For 2021
Now Azure Databricks achieves 50 times better performance thanks to a highly optimized version of Spark. Databricks also enables real-time co-authoring and automates versioning. Besides, it features runtimes optimized for machine learning that include many popular libraries, such as PyTorch, TensorFlow, Keras, etc.

Informatica Reviews

Best ETL Tools: A Curated List
Harder to Learn: Informatica offers many features and works well for larger teams, but Informatica Cloud takes more time to learn than modern ELT and ETL tools.
Source: estuary.dev
Top MuleSoft Alternatives for ITSM Leaders in 2025
Informatica focuses on amplifying data integration capabilities as part of its IDMC, offering a wide range of services for robust data management and integration strategies. It prioritizes data-centric integration with extensive features for governance, quality, and transformation, making it suitable for organizations emphasizing a unified data management approach....
Source: www.oneio.cloud
Top 11 Fivetran Alternatives for 2024
Informatica offered one of the first ETL products, Powercenter, in 1993, and one of the first cloud integration products, Informatica Cloud, in 2006. Informatica Cloud was originally built based on an older version of Informatica PowerCenter and eventually upgraded to a newer version of the on premises data integration based on Hadoop, then Spark.
Source: estuary.dev
Top 6 Mulesoft Alternatives & Competitors in 2024
Informatica Integration Cloud offers a comprehensive suite of integration solutions, including data integration, application integration, and API management. With its user-friendly interface and extensive connectivity options, Informatica poses a strong alternative to Mulesoft. Informatica supports connectivity to a broad range of data sources and targets, including...
Source: www.astera.com
The Best MuleSoft Alternatives [2024]
Informatica is an AI-powered, cloud-based data management platform that automates workflows and business processes.
Source: exalate.com

Social recommendations and mentions

Based on our record, Databricks seems to be more popular. It has been mentiond 18 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Databricks mentions (18)

  • Platform Engineering Abstraction: How to Scale IaC for Enterprise
    Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / 7 months ago
  • dolly-v2-12b
    Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 2 years ago
  • Clickstream data analysis with Databricks and Redpanda
    Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / over 2 years ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / almost 3 years ago
  • A Quick Start to Databricks on AWS
    Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 3 years ago
View more

Informatica mentions (0)

We have not tracked any mentions of Informatica yet. Tracking of Informatica recommendations started around Mar 2021.

What are some alternatives?

When comparing Databricks and Informatica, you can also consider the following products

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)

Rakam - Custom analytics platform

Concurrent - Concurrent is a technology solution providing real-time computing solutions for businesses and individuals.