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Oracle Database 12c VS Apache Arrow

Compare Oracle Database 12c VS Apache Arrow and see what are their differences

Oracle Database 12c logo Oracle Database 12c

Simplify database management and automate the information lifecycle with maximum security.

Apache Arrow logo Apache Arrow

Apache Arrow is a cross-language development platform for in-memory data.
  • Oracle Database 12c Landing page
    Landing page //
    2023-09-30
  • Apache Arrow Landing page
    Landing page //
    2021-10-03

Oracle Database 12c features and specs

  • Multi-tenant Architecture
    Oracle Database 12c introduces a multi-tenant architecture that allows a single container database to hold many pluggable databases, which makes it easier to consolidate databases and manage them collectively.
  • In-Memory Processing
    This feature allows data to be stored in memory, significantly improving query performance and providing real-time analytics capabilities.
  • Advanced Security
    Enhanced security features, including data redaction, key management, and robust auditing, ensure compliance with regulatory requirements and protect sensitive data.
  • Automated Management
    Oracle Database 12c offers advanced automation capabilities for routine tasks such as backup, patching, and tuning, reducing administrative overhead and operational costs.
  • Scalability
    This version supports scalability and high availability features, including Real Application Clusters (RAC) and Data Guard, making it suitable for enterprise-level applications.

Possible disadvantages of Oracle Database 12c

  • Complexity
    Oracle Database 12c is complex to set up and manage, requiring specialized knowledge and skills, which can result in increased operational complexity.
  • Cost
    The licensing and maintenance costs for Oracle Database 12c can be prohibitively high, especially for small and mid-sized enterprises.
  • Resource Intensive
    The database system is resource-intensive, necessitating high-performing hardware and considerable memory and storage resources.
  • Compatibility Issues
    There may be compatibility issues with older versions of applications and databases that do not support or integrate well with Oracle Database 12c.
  • Learning Curve
    Due to its extensive feature set and complex architecture, there is a steep learning curve for new users and administrators, which may require comprehensive training and certification.

Apache Arrow features and specs

  • In-Memory Columnar Format
    Apache Arrow stores data in a columnar format in memory which allows for efficient data processing and analytics by enabling operations on entire columns at a time.
  • Language Agnostic
    Arrow provides libraries in multiple languages such as C++, Java, Python, R, and more, facilitating cross-language development and enabling data interchange between ecosystems.
  • Interoperability
    Arrow's ability to act as a data transfer protocol allows easy interoperability between different systems or applications without the need for serialization or deserialization.
  • Performance
    Designed for high performance, Arrow can handle large data volumes efficiently due to its zero-copy reads and SIMD (Single Instruction, Multiple Data) operations.
  • Ecosystem Integration
    Arrow integrates well with various data processing systems like Apache Spark, Pandas, and more, making it a versatile choice for data applications.

Possible disadvantages of Apache Arrow

  • Complexity
    The use of Apache Arrow can introduce additional complexity, especially for smaller projects or those which do not require high-performance data interchange.
  • Learning Curve
    Getting accustomed to Apache Arrow can take time due to its unique in-memory format and APIs, especially for developers who are new to columnar data processing.
  • Memory Usage
    While Arrow excels in speed and performance, the memory consumption can be higher compared to row-based storage formats, potentially becoming a bottleneck.
  • Maturity
    Although rapidly evolving, some Arrow components or language implementations may not be as mature or feature-complete, potentially leading to limitations in certain use cases.
  • Integration Challenges
    While Arrow aims for broad compatibility, integrating it into existing systems may require substantial effort, affecting development timelines.

Analysis of Oracle Database 12c

Overall verdict

  • Oracle Database 12c is considered a strong option for large enterprises and organizations requiring a high-performance, scalable database solution with advanced features and robust support. It is well-suited for environments that need improved resource management, high availability, and enhanced security.

Why this product is good

  • Oracle Database 12c is a highly robust and enterprise-grade database management system known for its scalability, performance, and comprehensive features. It offers improvements over previous versions, particularly with the introduction of a multi-tenant architecture, which simplifies consolidation and management of databases. It also provides advanced security features, strong data integrity, and wide support for various data management needs.

Recommended for

  • Large enterprises
  • Organizations managing multiple databases
  • Businesses requiring high availability and reliability
  • Projects with complex data management needs
  • Entities needing advanced security and compliance

Oracle Database 12c videos

Koenig Solutions Training Review For Oracle Database 12c and Oracle EBS Training

More videos:

  • Review - Koenig Solutions Training Review For Oracle Database 12C: Backup and Recovery
  • Review - Using Virtual Private Database with Oracle Database 12c

Apache Arrow videos

Wes McKinney - Apache Arrow: Leveling Up the Data Science Stack

More videos:

  • Review - "Apache Arrow and the Future of Data Frames" with Wes McKinney
  • Review - Apache Arrow Flight: Accelerating Columnar Dataset Transport (Wes McKinney, Ursa Labs)

Category Popularity

0-100% (relative to Oracle Database 12c and Apache Arrow)
Databases
72 72%
28% 28
Relational Databases
100 100%
0% 0
Big Data
0 0%
100% 100
Tool
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Apache Arrow seems to be more popular. It has been mentiond 41 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.

Oracle Database 12c mentions (0)

We have not tracked any mentions of Oracle Database 12c yet. Tracking of Oracle Database 12c recommendations started around Mar 2021.

Apache Arrow mentions (41)

  • Sharing memory between processes with java.lang.foreign and jextract
    In another article of this series we'll plug these shared memory optimizations into Apache Arrow and share its buffers and vectors between apps (Java and/or Python). Then, with the help of another native library, we'll also add some GPU-processing power to the same Apache Arrow vectors. - Source: dev.to / 13 days ago
  • Show HN: Typed-arrow – compile‑time Arrow schemas for Rust
    I had no idea what Arrow is: https://arrow.apache.org or arrow-rs: https://github.com/apache/arrow-rs. - Source: Hacker News / about 1 year ago
  • Show HN: Pontoon, an open-source data export platform
    - Open source: Pontoon is free to use by anyone Under the hood, we use Apache Arrow (https://arrow.apache.org/) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute. In the shorter-term, there are several improvements we want to make, like:. - Source: Hacker News / about 1 year ago
  • Unlocking DuckDB from Anywhere - A Guide to Remote Access with Apache Arrow and Flight RPC (gRPC)
    Apache Arrow : It contains a set of technologies that enable big data systems to process and move data fast. - Source: dev.to / over 1 year ago
  • Using Polars in Rust for high-performance data analysis
    One of the main selling points of Polars over similar solutions such as Pandas is performance. Polars is written in highly optimized Rust and uses the Apache Arrow container format. - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing Oracle Database 12c and Apache Arrow, you can also consider the following products

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

MySQL - The world's most popular open source database

Apache Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.