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Redis ™ VS Azure Databricks

Compare Redis VS Azure Databricks and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Redis logo Redis

Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Azure Databricks logo Azure Databricks

Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

  • Azure Databricks Landing page
    Landing page //
    2023-04-02

Redis features and specs

  • Performance
    Redis is an in-memory data store, which allows it to provide extremely fast read and write operations. This makes it ideal for applications requiring real-time interactions.
  • Data Structures
    Redis offers a variety of data structures, such as strings, hashes, lists, sets, and sorted sets. This flexibility helps developers manage data more efficiently in different scenarios.
  • Scalability
    Redis supports horizontal scalability with features like clustering and partitioning, allowing for easy scaling as your application grows.
  • Persistence
    Though primarily an in-memory store, Redis provides options for data persistence, such as RDB snapshots and AOF logs, enabling data durability across reboots.
  • Pub/Sub Messaging
    Redis includes a built-in publish/subscribe messaging system, which can be used to implement real-time messaging and notifications.
  • Simple API
    Redis has a simple and intuitive API, which can speed up development time and make it easier to integrate Redis into various application stacks.
  • Atomic Operations
    Redis supports atomic operations on data structures, reducing the complexity of concurrent programming and making it easier to maintain data consistency.

Possible disadvantages of Redis

  • Memory Usage
    Being an in-memory data store, Redis can become expensive in terms of memory usage, especially when working with large datasets.
  • Data Persistence Limitations
    While Redis offers data persistence, it is not as robust as traditional databases. There can be data loss in certain configurations, such as when using asynchronous persistence methods.
  • Complexity in Scaling
    Although Redis supports clustering, setting up and managing a Redis cluster can be complex and may require significant DevOps expertise.
  • Single-threaded Nature
    Redis operates on a single-threaded event loop, which can become a bottleneck for certain workloads that could benefit from multi-threading.
  • Limited Query Capabilities
    Compared to traditional relational databases, Redis offers limited querying capabilities. Complex queries and joins are not supported natively.
  • License
    As of Redis 6 and higher, the Redis modules are under the Server Side Public License (SSPL), which may be restrictive for some use cases compared to more permissive open-source licenses.

Azure Databricks features and specs

  • Scalability
    Azure Databricks enables easy scaling of workloads up or down, allowing users to handle large volumes of data and perform distributed processing efficiently.
  • Integration
    Seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure SQL Data Warehouse, facilitating a streamlined data pipeline.
  • Collaboration
    Offers collaborative features like notebooks that allow multiple users to work together easily on data analytics projects.
  • Performance Optimization
    Built on top of Apache Spark, Azure Databricks provides high performance and optimized execution for data engineering and machine learning tasks.
  • Managed Service
    As a fully managed service, it handles infrastructure provisioning and maintenance, enabling users to focus on data insights rather than backend management.

Possible disadvantages of Azure Databricks

  • Cost
    Azure Databricks can be expensive, particularly for large-scale and long-running workloads, which may be a concern for budget-conscious organizations.
  • Complexity
    Despite its capabilities, Azure Databricks may have a steep learning curve, especially for users not familiar with Apache Spark.
  • Vendor Lock-in
    Leveraging Azure-specific services can lead to vendor lock-in, making it challenging to migrate workloads and data to other cloud platforms.
  • Limited Offline Capabilities
    As a cloud-native service, it requires an active internet connection and might not suit scenarios that require offline processing.
  • Compliance Concerns
    Due to Azure Databricks' integration with Azure, users need to carefully manage compliance and data governance, which might be complex in multi-regional deployments.

Redis videos

+ Add

What is Redis? | Why and When to use Redis? | Tech Primers

More videos:

  • Review - Improve your Redis developer experience with RedisInsight, Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Azure Databricks videos

+ Add

Azure Databricks is Easier Than You Think

More videos:

  • Review - Ingest, prepare & transform using Azure Databricks & Data Factory | Azure Friday
  • Review - Azure Databricks - What's new! | DB102

Category Popularity

0-100% (relative to Redis and Azure Databricks)

Redis

Azure Databricks

Databases
100 100%
Databases
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Office & Productivity
0 0%
Office & Productivity
100% 100

User comments

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Reviews

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

Redis Reviews

Redis Alternative for App Performance | Gigaspaces
Redis offers a RESTful API for accessing data stored within its in-memory technology data structures. This API provides a simple and efficient way to interact with Redis, enabling developers to leverage its capabilities seamlessly in their applications. Developers also need to manage the Redis cached data lifecycle, it’s the application responsibility to store the data &...
Source: www.gigaspaces.com
Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Source: news.ycombinator.com
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Source: engineering.kablamo.com.au
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.
Source: www.spec-india.com

Azure Databricks Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Azure Databricks is a data analytics tool optimized for Microsoft’s Azure cloud services solution. It provides three development environments for data-intensive apps, namely Databricks SQL, Databricks Machine Learning, and Databricks Data Science & Engineering.The platform supports languages including Python, Java, R, Scala, and SQL, plus data science frameworks and...
Source: theqalead.com

Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than Azure Databricks. While we know about 217 links to Redis, we've tracked only 2 mentions of Azure Databricks. 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.

Redis mentions (217)

  • Feature Comparison: Reliable Queue vs. Valkey and Redis Stream
    Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature. - Source: dev.to / 1 day ago
  • Finding Bigfoot with Async Generators + TypeScript
    Of course, these examples are just toys. A more proper use for asynchronous generators is handling things like reading files, accessing network services, and calling slow running things like AI models. So, I'm going to use an asynchronous generator to access a networked service. That service is Redis and we'll be using Node Redis and Redis Query Engine to find Bigfoot. - Source: dev.to / 15 days ago
  • Caching Isn’t Always the Answer – And Here’s Why
    Slap on some Redis, sprinkle in a few set() calls, and boom—10x faster responses. - Source: dev.to / 15 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Real-time serving: Many push processed data into low-latency serving layers like Redis to power applications needing instant responses (think fraud detection, live recommendations, financial dashboards). - Source: dev.to / 29 days ago
  • Setup a Redis Cluster using Redis Stack
    Redis® Cluster is a fully distributed implementation with automated sharding capabilities (horizontal scaling capabilities), designed for high performance and linear scaling up to 1000 nodes. . - Source: dev.to / about 2 months ago
View more

Azure Databricks mentions (2)

  • Top 30 Microsoft Azure Services
    In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 4 years ago
  • ZooKeeper-free Kafka is out. First Demo
    https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 4 years ago

What are some alternatives?

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

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

MicroStrategy - MicroStrategy is a cloud-based platform providing business intelligence, mobile intelligence and network applications.

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