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Apache Cassandra VS SAP Data Management

Compare Apache Cassandra VS SAP Data Management and see what are their differences

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Apache Cassandra logo Apache Cassandra

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

SAP Data Management logo SAP Data Management

Sap Data Management is a flagship enterprise information management solution that facilities the organizations to manage data quality, migration of data, text analytics, and interconnectivity with both SAP and non-SAP system.
  • Apache Cassandra Landing page
    Landing page //
    2022-04-17
  • SAP Data Management Landing page
    Landing page //
    2023-08-22

Apache Cassandra features and specs

  • Scalability
    Apache Cassandra is designed for linear scalability and can handle large volumes of data across many commodity servers without a single point of failure.
  • High Availability
    Cassandra ensures high availability by replicating data across multiple nodes. Even if some nodes fail, the system remains operational.
  • Performance
    It provides fast writes and reads by using a peer-to-peer architecture, making it highly suitable for applications requiring quick data access.
  • Flexible Data Model
    Cassandra supports a flexible schema, allowing users to add new columns to a table at any time, making it adaptable for various use cases.
  • Geographical Distribution
    Data can be distributed across multiple data centers, ensuring low-latency access for geographically distributed users.
  • No Single Point of Failure
    Its decentralized nature ensures there is no single point of failure, which enhances resilience and fault-tolerance.

Possible disadvantages of Apache Cassandra

  • Complexity
    Managing and configuring Cassandra can be complex, requiring specialized knowledge and skills for optimal performance.
  • Eventual Consistency
    Cassandra follows an eventual consistency model, meaning that there might be a delay before all nodes have the latest data, which may not be suitable for all use cases.
  • Write-heavy Operations
    Although Cassandra handles writes efficiently, write-heavy workloads can lead to compaction issues and increased read latency.
  • Limited Query Capabilities
    Cassandra's query capabilities are relatively limited compared to traditional RDBMS, lacking support for complex joins and aggregations.
  • Maintenance Overhead
    Regular maintenance tasks such as node repair and compaction are necessary to ensure optimal performance, adding to the administrative overhead.
  • Tooling and Ecosystem
    While the ecosystem for Cassandra is growing, it is still not as extensive or mature as those for some other database technologies.

SAP Data Management features and specs

  • Scalability
    SAP Data Management solutions are designed to scale with your business. They can handle vast amounts of data and are suitable for large enterprises as well as growing companies.
  • Integration
    SAP's Data Management tools offer seamless integration with other SAP applications and third-party systems, ensuring a unified data environment.
  • Real-time Data Processing
    One of the key features is real-time data processing, which enhances decision-making and enables businesses to react quickly to changing conditions.
  • Comprehensive Analytics
    The robust analytics tools within the SAP suite provide deep insights into your data, helping businesses to identify trends, make predictions, and optimize operations.
  • Data Security
    SAP places a strong emphasis on data security, with built-in features to ensure data integrity, confidentiality, and compliance with regulatory requirements.
  • Support and Community
    SAP provides extensive support and has a large user community, which can be very beneficial for troubleshooting and optimizing the use of their data management tools.

Possible disadvantages of SAP Data Management

  • Cost
    SAP solutions can be expensive to implement and maintain, making them less accessible for small businesses or startups with limited budgets.
  • Complexity
    The extensive feature set and capabilities can make SAP Data Management tools complex to configure and use, often requiring specialized knowledge and training.
  • Implementation Time
    Deploying SAP Data Management solutions can be time-consuming, often requiring months of planning, customization, and integration.
  • Resource Intensive
    Running SAP Data Management tools effectively can require significant IT resources, including powerful hardware and skilled personnel.
  • Customization Challenges
    While highly customizable, SAP’s systems can be difficult to tailor exactly to a company’s specific needs without extensive development work.

Apache Cassandra videos

Course Intro | DS101: Introduction to Apache Cassandra™

More videos:

  • Review - Introduction to Apache Cassandra™

SAP Data Management videos

No SAP Data Management videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Apache Cassandra and SAP Data Management)
Databases
100 100%
0% 0
Data Integration
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
OS & Utilities
0 0%
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 Apache Cassandra and SAP Data Management

Apache Cassandra Reviews

16 Top Big Data Analytics Tools You Should Know About
Application Areas: If you want to work with SQL-like data types on a No-SQL database, Cassandra is a good choice. It is a popular pick in the IoT, fraud detection applications, recommendation engines, product catalogs and playlists, and messaging applications, providing fast real-time insights.
9 Best MongoDB alternatives in 2019
The Apache Cassandra is an ideal choice for you if you want scalability and high availability without affecting its performance. This MongoDB alternative tool offers support for replicating across multiple datacenters.
Source: www.guru99.com

SAP Data Management Reviews

We have no reviews of SAP Data Management yet.
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Social recommendations and mentions

Based on our record, Apache Cassandra seems to be more popular. It has been mentiond 44 times since March 2021. 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.

Apache Cassandra mentions (44)

  • Why You Shouldn’t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / 21 days ago
  • Data integrity in Ably Pub/Sub
    All messages are persisted durably for two minutes, but Pub/Sub channels can be configured to persist messages for longer periods of time using the persisted messages feature. Persisted messages are additionally written to Cassandra. Multiple copies of the message are stored in a quorum of globally-distributed Cassandra nodes. - Source: dev.to / 6 months ago
  • Which Database is Perfect for You? A Comprehensive Guide to MySQL, PostgreSQL, NoSQL, and More
    Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers without a single point of failure. - Source: dev.to / 11 months ago
  • Consistent Hashing: An Overview and Implementation in Golang
    Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / about 1 year ago
  • Understanding SQL vs. NoSQL Databases: A Beginner's Guide
    On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra. - Source: dev.to / about 1 year ago
View more

SAP Data Management mentions (0)

We have not tracked any mentions of SAP Data Management yet. Tracking of SAP Data Management recommendations started around Aug 2021.

What are some alternatives?

When comparing Apache Cassandra and SAP Data Management, you can also consider the following products

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

Ataccama - We deliver Self-Driving Data Management & Governance with Ataccama ONE. It’s a fully integrated yet modular platform for any data, user, domain, or deployment.

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

Dell EMC DataIQ - Dell EMC DataIQ is one of the unique storage monitoring and dataset management software for unstructured data that allows a unified file system of PowerScale, ECS, and delivers unique insights into data usage and storage system health.

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

1010Data - 1010data provides cloud-based big data analytics for retail, manufacturing, telecom and financial services enterprises.