Confluent vs Databricks comparison

Confluent is an enterprise-ready, full-scale streaming platform that enhances Apache Kafka. 

Confluent has integrated cutting-edge features that are designed to enhance these tasks: 

• Speed up application development and connectivity
• Enable transformations through stream processing
• Streamline business operations at scale
• Adhere to strict architectural standards

Confluent is a more complete distribution of Kafka in that it enhances the integration possibilities of Kafka by introducing tools for managing and optimizing Kafka clusters while providing methods for making sure the streams are secure. Confluent supports publish-and-subscribe as well as the storing and processing of data within the streams. Kafka is easier to operate and build thanks to Confluent.

Confluent's software is available in three different varieties: 

1. A free, open-source streaming platform that makes it simple to start using real-time data streams
2. An enterprise-grade version of the product with more administrative, ops, and monitoring tools
3. A premium cloud-based version.

Confluent Advantage Features

Confluent has many valuable key features. Some of the most useful ones include:

• Multi-language
  
  
  • Clients: C++, Python, Go, and .NET
  • REST proxy: Can connect to Kafka from any connected network device
  • Admin REST APIs: RESTful interface for performing administrator operations

• Pre-built ecosystem
  
  
  • Connectors: More than 100 supported connectors, including S3, Elastic, HDFS, JDBC
  • MQTT proxy: Gain access to Kafka from MQTT gateways and devices
  • Schema registry: Centralized database to guarantee data compatibility

• Streaming database
  
  
  • ksqlDB: Materialized views and real-time stream processing

• GUI management 
  
  
  • Control panel: GUI for scalable Kafka management and monitoring
  • Health+: Smart alerts and cloud-based control centers

• DevOps automation that is flexible
  
  
  • Confluent for Kubernetes: Complete API to deploy on Kubernetes
  • Automated Ansible deployment on non-containerized environments

• Dynamic performance 
  
  
  • Self-balancing clusters: Automated partition re-balancing across brokers in the cluster
  • Tiered storage: Older Kafka data offloading to object storage with transparent access

• Security that is enterprise-grade 
  
  
  • Role-based access control: Granular user/group access authorization
  • Audit logs that are structured: Logs of user actions kept in dedicated Kafka topics
  • Secret protection: Sensitive information is encrypted

• Global resilience
  
  
  • Linking clusters: A real-time, highly reliable, and consistent bridge across on-premises and cloud environments
  • Multiple-region clusters: Single Kafka cluster with automated client failover distributed across multiple data centers
  • Replicator: Asynchronous replication that is based on the Kafka Connect framework

• Support
  
  
  • Round the clock enterprise support from Kafka experts

Reviews from Real Users

Confluent stands out among its competitors for a number of reasons. Two major ones are its robust enterprise support and its open source option. PeerSpot users take note of the advantages of these features in their reviews: 

Ravi B., a solutions architect at a tech services company, writes of the solution, “KSQL is a valuable feature, as is the Kafka Connect framework for connecting to the various source systems where you need not write the code. We get great support from Confluent because we're using the enterprise version and whenever there's a problem, they support us with fine-tuning and finding the root cause.”

Amit S., an IT consultant, notes, “The biggest benefit is that it is open source. You have the flexibility of opting or not opting for enterprise support, even though the tool itself is open source.” He adds, “The second benefit is it's very modern and built on Java and Scala. You can extend the features very well, and it doesn't take a lot of effort to do so.”

Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.

Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.

Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.

Databricks Key Features

Some of Databricks key features include:

• Cloud-native: Works well on any prominent cloud provider.
  
• Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
  
• Self-governance: Built-in governance and security controls.
  
• Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
  
• Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
  
• Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
  
• Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
  
• Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.

Reviews from Real Users

Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.

PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”

A business intelligence coordinator in construction notes, “The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.”

An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”