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Redis vs SAP HANA: What are the differences?

Redis vs SAP HANA

Redis and SAP HANA are both popular in-memory data stores used in different scenarios. While they have some similarities, they also have key differences that set them apart from each other. In this article, we will explore six key differences between Redis and SAP HANA.

  1. Data Model: Redis is a key-value store that allows you to store simple data structures like strings, lists, sets, and hashes. On the other hand, SAP HANA is a fully-fledged relational database management system (RDBMS) that supports SQL queries and complex data models like tables, views, and stored procedures. This makes SAP HANA suitable for handling structured data and performing sophisticated analytics.

  2. Scalability: Redis offers built-in support for distributed caching and data replication, allowing you to scale horizontally by adding more Redis nodes. However, SAP HANA provides scaling options through vertical and horizontal scaling, allowing you to increase the computational power and storage capacity of the system as your needs grow. SAP HANA's scalability options make it more suitable for handling large volumes of data and complex workloads.

  3. Query Language: Redis does not have a built-in query language like SQL. Instead, it provides a set of commands for data manipulation and retrieval. In contrast, SAP HANA uses SQL as its query language, allowing you to perform complex queries and aggregations on the data stored in the system. SQL's expressive power makes SAP HANA a more flexible choice for querying and analyzing data.

  4. Data Persistence: Redis offers both in-memory and disk-based data persistence options. You can configure Redis to periodically save snapshots of the in-memory data to disk or append changes to a log file for durability. On the other hand, SAP HANA stores data persistently on disk by default, ensuring data durability even in the event of a system failure. This makes SAP HANA more suitable for storing critical and persistent data.

  5. Use Cases: Redis is commonly used for caching, session management, and real-time analytics due to its low latency and high throughput capabilities. Its simplicity and fast data access make it a good choice for applications that require rapid data retrieval. However, SAP HANA is preferred for scenarios that involve complex data processing, predictive analytics, and real-time data integration. Its advanced features enable businesses to derive actionable insights from their data and make data-driven decisions.

  6. Cost: Redis is an open-source solution that can be used free of charge. However, if you require additional features or enterprise-level support, you may need to purchase a commercial license or subscribe to a managed Redis service. On the other hand, SAP HANA is a proprietary software that requires licensing fees. The cost of SAP HANA can vary depending on the edition and deployment options chosen. It is essential to consider the overall cost of ownership when deciding between Redis and SAP HANA.

In summary, Redis and SAP HANA differ in terms of their data model, scalability options, query language, data persistence, use cases, and cost. Understanding these differences is crucial for selecting the right data store based on the specific requirements and constraints of your application or system.

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Pros of Redis
Pros of SAP HANA
  • 886
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
  • 155
  • 121
  • 42
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
  • 22
    Great community
  • 22
  • 19
    "NoSQL" key-value data store
  • 16
  • 13
  • 11
    Sorted Sets
  • 10
  • 10
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
  • 5
    Awesomeness for Free
  • 5
  • 4
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
  • 5
  • 5
  • 4
  • 4
  • 2
  • 2
  • 2
  • 2
  • 1

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Cons of Redis
Cons of SAP HANA
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
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    What is Redis?

    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

    What is SAP HANA?

    It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

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    Nov 20 2019 at 3:38AM


    Jun 6 2019 at 5:11PM


    What are some alternatives to Redis and SAP HANA?
    Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    See all alternatives