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LibreOffice - Base VS Apache Spark

Compare LibreOffice - Base VS Apache Spark and see what are their differences

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

LibreOffice - Base logo LibreOffice - Base

Base, database, database frontend, LibreOffice, ODF, Open Standards, SQL, ODBC

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
  • LibreOffice - Base Landing page
    Landing page //
    2021-10-15
  • Apache Spark Landing page
    Landing page //
    2021-12-31

LibreOffice - Base features and specs

  • Cost
    LibreOffice Base is free and open-source, which makes it a cost-effective alternative to other database management systems.
  • Compatibility
    It is compatible with a wide range of databases including MySQL, PostgreSQL, and Microsoft Access files, which enhances flexibility.
  • Cross-Platform
    LibreOffice Base runs on multiple platforms including Windows, macOS, and Linux, offering flexibility to users on different systems.
  • Open Standards
    It supports open standards for file formats, promoting interoperability and long-term data management.
  • User Community
    Being part of the LibreOffice suite, it has a strong user community and extensive documentation, providing ample support resources.

Possible disadvantages of LibreOffice - Base

  • Performance
    Compared to proprietary database management systems, LibreOffice Base may have slower performance and lower efficiency for large datasets.
  • Complexity
    The interface and functionalities may be challenging for new users who are not familiar with database management concepts.
  • Limited Advanced Features
    It lacks some advanced features found in other enterprise-level database solutions, making it less suitable for very complex database applications.
  • Infrequent Updates
    Updates and new features tend to be less frequent compared to commercial software, potentially leading to longer periods with unresolved bugs or missing features.
  • Technical Support
    While there is a strong community, there is no official professional technical support, which can be a drawback for businesses requiring reliable and immediate assistance.

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

LibreOffice - Base videos

+ Add

LibreOffice Base (01) Create a Database, Create a Table

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to LibreOffice - Base and Apache Spark)

LibreOffice - Base

Apache Spark

Databases
47 47%
Databases
53% 53
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Big Data
0 0%
Big Data
100% 100
Development
100 100%
Development
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare LibreOffice - Base and Apache Spark

LibreOffice - Base Reviews

TOP best Microsoft Access replacement software for databases
LibreOffice Base has a host of handy features, including cross-database support for multi-user databases such as MySQL, Adabas D, Microsoft Access, and PostgreSQL. LibreOffice Base is probably an almost direct copy of Microsoft Access. Both are front-end database management tools.
Source: tipsmake.com

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Apache Spark seems to be more popular. It has been mentiond 70 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.

LibreOffice - Base mentions (0)

We have not tracked any mentions of LibreOffice - Base yet. Tracking of LibreOffice - Base recommendations started around Mar 2021.

Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 1 month ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 1 month ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 2 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing LibreOffice - Base and Apache Spark, you can also consider the following products

Microsoft Office Access - Access is now much more than a way to create desktop databases. It’s an easy-to-use tool for quickly creating browser-based database applications.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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

Hadoop - Open-source software for reliable, scalable, distributed computing

My Visual Database - Using My Visual Database, you can create databases for invoicing, inventory, CRM, or any specific purpose.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

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