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SAP HANA

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140
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Sybase

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SAP HANA vs Sybase: What are the differences?

SAP HANA is an in-memory database and application platform, while Sybase is a relational database management system (RDBMS). Let's explore the key differences between them.

  1. Performance: SAP HANA is an in-memory database platform, which means it stores data in RAM for faster processing. On the other hand, Sybase is a disk-based database system. This difference in storage mechanism gives SAP HANA a significant performance advantage over Sybase, allowing for faster data retrieval and processing.

  2. Data Processing Capability: SAP HANA is specifically designed for real-time data processing and analytics. It supports complex analytical queries, predictive analytics, and text analysis. Sybase, on the other hand, focuses more on transactional processing and does not provide as advanced analytical capabilities as SAP HANA.

  3. Data Compression: SAP HANA offers advanced data compression techniques that significantly reduce the storage footprint. This allows for efficient storage utilization and reduces the overall storage costs. Sybase, on the other hand, does not have the same level of data compression capabilities as SAP HANA.

  4. Scale-out Architecture: SAP HANA supports a scale-out architecture, which means it can be distributed across multiple servers to handle large data volumes and deliver higher performance. Sybase, on the other hand, primarily operates on a scale-up architecture, where the system is designed to handle increased workloads on a single server.

  5. Data Replication: SAP HANA provides built-in data replication capabilities for real-time data integration and synchronization. It allows for seamless data replication between different systems and databases. Sybase, on the other hand, relies on external tools and processes for data replication.

  6. Integration with SAP Applications: SAP HANA is tightly integrated with other SAP applications, such as SAP Business Suite and SAP S/4HANA. This integration allows for seamless data exchange and real-time insights. Sybase, although owned by SAP, does not offer the same level of integration with SAP applications as SAP HANA.

In summary, SAP HANA revolutionizes data processing with its in-memory computing capabilities, allowing real-time analytics and decision-making, whereas Sybase is a traditional RDBMS known for its reliability and performance in transaction processing. While SAP HANA offers cutting-edge technology for modern business needs, Sybase continues to provide robust solutions for traditional database requirements.

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    In-memory
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    SQL
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    Distributed
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    Performance
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    Realtime
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    Concurrent
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    OLAP
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    OLTP
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    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.

    What is Sybase?

    Modernize and accelerate your transaction-based applications on premise and in the cloud. This high-performance SQL database server uses a relational management model to meet rising demand for performance, reliability, and efficiency in every industry.

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    What companies use SAP HANA?
    What companies use Sybase?
    See which teams inside your own company are using SAP HANA or Sybase.
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    What tools integrate with SAP HANA?
    What tools integrate with Sybase?

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    What are some alternatives to SAP HANA and Sybase?
    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 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
    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 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
    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.
    See all alternatives