Alternatives to SAP HANA logo

Alternatives to SAP HANA

Oracle, Snowflake, Hadoop, Redis, and Hazelcast are the most popular alternatives and competitors to SAP HANA.
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What is SAP HANA and what are its top alternatives?

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.
SAP HANA is a tool in the In-Memory Databases category of a tech stack.

Top Alternatives to SAP HANA

  • Oracle
    Oracle

    Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database. ...

  • Snowflake
    Snowflake

    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn. ...

  • Hadoop
    Hadoop

    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. ...

  • Redis
    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. ...

  • Hazelcast
    Hazelcast

    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. ...

  • Aerospike
    Aerospike

    Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees. ...

  • MemSQL
    MemSQL

    MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines. ...

  • Apache Ignite
    Apache Ignite

    It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale ...

SAP HANA alternatives & related posts

Oracle logo

Oracle

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An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism
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PROS OF ORACLE
  • 42
    Reliable
  • 31
    Enterprise
  • 15
    High Availability
  • 5
    Expensive
  • 5
    Hard to maintain
  • 4
    Maintainable
  • 3
    High complexity
  • 3
    Hard to use
CONS OF ORACLE
  • 13
    Expensive

related Oracle posts

Hi. We are planning to develop web, desktop, and mobile app for procurement, logistics, and contracts. Procure to Pay and Source to pay, spend management, supplier management, catalog management. ( similar to SAP Ariba, gap.com, coupa.com, ivalua.com vroozi.com, procurify.com

We got stuck when deciding which technology stack is good for the future. We look forward to your kind guidance that will help us.

We want to integrate with multiple databases with seamless bidirectional integration. What APIs and middleware available are best to achieve this? SAP HANA, Oracle, MySQL, MongoDB...

ASP.NET / Node.js / Laravel. ......?

Please guide us

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Snowflake logo

Snowflake

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The data warehouse built for the cloud
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885
+ 1
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PROS OF SNOWFLAKE
  • 4
    Public and Private Data Sharing
  • 3
    Good Performance
  • 2
    Serverless
  • 2
    Multicloud
  • 2
    Great Documentation
  • 2
    User Friendly
  • 1
    Usage based billing
  • 1
    Innovative
  • 1
    Economical
CONS OF SNOWFLAKE
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    related Snowflake posts

    Shared insights
    on
    Google BigQueryGoogle BigQuerySnowflakeSnowflake

    I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.

    What's nice too is that it has SQL-based ML tools, and it has great GIS support!

    See more
    Shared insights
    on
    SnowflakeSnowflakeHadoopHadoopMarkLogicMarkLogic

    For a property and casualty insurance company, we currently use MarkLogic and Hadoop for our raw data lake. Trying to figure out how snowflake fits in the picture. Does anybody have some good suggestions/best practices for when to use and what data to store in Mark logic versus Snowflake versus a hadoop or all three of these platforms redundant with one another?

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    Hadoop logo

    Hadoop

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    Open-source software for reliable, scalable, distributed computing
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    PROS OF HADOOP
    • 38
      Great ecosystem
    • 11
      One stack to rule them all
    • 4
      Great load balancer
    • 1
      Amazon aws
    • 1
      Java syntax
    CONS OF HADOOP
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      related Hadoop posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 7 upvotes · 1.1M views

      Why we built Marmaray, an open source generic data ingestion and dispersal framework and library for Apache Hadoop :

      Built and designed by our Hadoop Platform team, Marmaray is a plug-in-based framework built on top of the Hadoop ecosystem. Users can add support to ingest data from any source and disperse to any sink leveraging the use of Apache Spark . The name, Marmaray, comes from a tunnel in Turkey connecting Europe and Asia. Similarly, we envisioned Marmaray within Uber as a pipeline connecting data from any source to any sink depending on customer preference:

      https://eng.uber.com/marmaray-hadoop-ingestion-open-source/

      (Direct GitHub repo: https://github.com/uber/marmaray Kafka Kafka Manager )

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      Shared insights
      on
      KafkaKafkaHadoopHadoop
      at

      The early data ingestion pipeline at Pinterest used Kafka as the central message transporter, with the app servers writing messages directly to Kafka, which then uploaded log files to S3.

      For databases, a custom Hadoop streamer pulled database data and wrote it to S3.

      Challenges cited for this infrastructure included high operational overhead, as well as potential data loss occurring when Kafka broker outages led to an overflow of in-memory message buffering.

      See more
      Redis logo

      Redis

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      Open source (BSD licensed), in-memory data structure store
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      PROS OF REDIS
      • 879
        Performance
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        Super fast
      • 511
        Ease of use
      • 441
        In-memory cache
      • 321
        Advanced key-value cache
      • 190
        Open source
      • 179
        Easy to deploy
      • 163
        Stable
      • 152
        Free
      • 120
        Fast
      • 40
        High-Performance
      • 39
        High Availability
      • 34
        Data Structures
      • 32
        Very Scalable
      • 23
        Replication
      • 20
        Great community
      • 19
        Pub/Sub
      • 17
        "NoSQL" key-value data store
      • 14
        Hashes
      • 12
        Sets
      • 10
        Sorted Sets
      • 9
        Lists
      • 8
        BSD licensed
      • 8
        NoSQL
      • 7
        Async replication
      • 7
        Integrates super easy with Sidekiq for Rails background
      • 7
        Bitmaps
      • 6
        Open Source
      • 6
        Keys with a limited time-to-live
      • 5
        Strings
      • 5
        Lua scripting
      • 4
        Awesomeness for Free!
      • 4
        Hyperloglogs
      • 3
        outstanding performance
      • 3
        Runs server side LUA
      • 3
        Networked
      • 3
        LRU eviction of keys
      • 3
        Written in ANSI C
      • 3
        Feature Rich
      • 3
        Transactions
      • 2
        Data structure server
      • 2
        Performance & ease of use
      • 1
        Existing Laravel Integration
      • 1
        Automatic failover
      • 1
        Easy to use
      • 1
        Object [key/value] size each 500 MB
      • 1
        Simple
      • 1
        Channels concept
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        Scalable
      • 1
        Temporarily kept on disk
      • 1
        Dont save data if no subscribers are found
      • 0
        Jk
      CONS OF REDIS
      • 14
        Cannot query objects directly
      • 2
        No secondary indexes for non-numeric data types
      • 1
        No WAL

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      Robert Zuber

      We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

      As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

      When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

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      I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

      We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

      Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

      We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

      Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

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      Hazelcast logo

      Hazelcast

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      Clustering and highly scalable data distribution platform for Java
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      PROS OF HAZELCAST
      • 10
        High Availibility
      • 6
        Distributed Locking
      • 5
        Distributed compute
      • 5
        Sharding
      • 4
        Load balancing
      • 3
        Sql query support in cluster wide
      • 3
        Map-reduce functionality
      • 3
        Written in java. runs on jvm
      • 3
        Publish-subscribe
      • 2
        Performance
      • 2
        Simple-to-use
      • 2
        Multiple client language support
      • 2
        Rest interface
      • 2
        Optimis locking for map
      • 1
        Super Fast
      • 1
        Admin Interface (Management Center)
      • 1
        Better Documentation
      • 1
        Easy to use
      CONS OF HAZELCAST
      • 3
        License needed for SSL

      related Hazelcast posts

      Aerospike logo

      Aerospike

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      Flash-optimized in-memory open source NoSQL database
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      PROS OF AEROSPIKE
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        Ram and/or ssd persistence
      • 12
        Easy clustering support
      • 5
        Easy setup
      • 4
        Acid
      • 3
        Scale
      • 3
        Performance better than Redis
      • 3
        Petabyte Scale
      • 2
        Ease of use
      CONS OF AEROSPIKE
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        MemSQL logo

        MemSQL

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        Database for real-time transactions and analytics.
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        PROS OF MEMSQL
        • 8
          Distributed
        • 4
          Realtime
        • 3
          JSON
        • 3
          Sql
        • 3
          Columnstore
        • 3
          Concurrent
        • 2
          Ultra fast
        • 2
          Scalable
        • 1
          Pipeline
        • 1
          Availability Group
        • 1
          S3
        • 1
          Mixed workload
        • 1
          Unlimited Storage Database
        CONS OF MEMSQL
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          Apache Ignite logo

          Apache Ignite

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          An open-source distributed database, caching and processing platform
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          PROS OF APACHE IGNITE
          • 4
            Written in java. runs on jvm
          • 4
            Free
          • 3
            Load balancing
          • 3
            Multiple client language support
          • 3
            Sql query support in cluster wide
          • 3
            Rest interface
          • 3
            High Avaliability
          • 2
            Better Documentation
          • 2
            Easy to use
          • 1
            Distributed compute
          • 1
            Distributed Locking
          CONS OF APACHE IGNITE
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