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Apache Parquet VS Amazon API Gateway

Compare Apache Parquet VS Amazon API Gateway and see what are their differences

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Apache Parquet logo Apache Parquet

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

Amazon API Gateway logo Amazon API Gateway

Create, publish, maintain, monitor, and secure APIs at any scale
  • Apache Parquet Landing page
    Landing page //
    2022-06-17
  • Amazon API Gateway Landing page
    Landing page //
    2023-03-12

Apache Parquet features and specs

  • Columnar Storage
    Apache Parquet uses columnar storage, which allows for efficient retrieval of only the data you need, reducing I/O and improving query performance on large datasets.
  • Compression
    Parquet files support efficient compression and encoding schemes, resulting in significant storage savings and less data to transfer over the network.
  • Compatibility
    It is compatible with the Hadoop ecosystem, including tools like Apache Spark, Hive, and Impala, making it versatile for big data processing.
  • Schema Evolution
    Parquet supports schema evolution, allowing changes to the schema without breaking existing data, which helps in maintaining long-lived data pipelines.
  • Efficient Read Performance for Aggregations
    Due to its columnar layout, Parquet is highly efficient for processing queries that aggregate data across columns, such as SUM and AVERAGE.

Possible disadvantages of Apache Parquet

  • Write Performance
    Writing data to Parquet can be slower compared to row-based formats, particularly for small inserts or updates, due to the overhead of encoding and compression.
  • Complexity in File Management
    Managing and partitioning Parquet files to optimize performance can become complex, particularly as datasets grow in size and complexity.
  • Not Ideal for All Workloads
    Workloads that require frequent row-level updates or involve small queries might be less efficient with Parquet due to its columnar nature.
  • Learning Curve
    The need to understand the nuances of columnar storage, encoding, and compression can pose a learning curve for teams new to Parquet.

Amazon API Gateway features and specs

  • Scalability
    API Gateway automatically scales to handle the number of requests your API receives, ensuring high availability and reliability.
  • Ease of Integration
    Seamlessly integrates with other AWS services like Lambda, DynamoDB, and IAM, enabling a cohesive environment for developing serverless applications.
  • Built-in Security
    Provides features such as IAM roles, API keys, and AWS WAF integration for safeguarding your APIs from potential threats.
  • Monitoring and Logging
    Supports CloudWatch integration for monitoring API requests and responses, helping you maintain observability and troubleshoot issues effectively.
  • Cost-Effective
    You only pay for the requests made to your APIs and the amount of data transferred out, making it a cost-effective solution for many use cases.
  • Caching
    Built-in caching at the API Gateway level can improve performance and reduce latency for frequently accessed data.

Possible disadvantages of Amazon API Gateway

  • Complexity in Configuration
    Setting up and managing API Gateway can be complex, especially for users who are not familiar with AWS services and cloud infrastructure.
  • Cold Start Latency
    When integrated with AWS Lambda, cold starts can introduce latency which can affect the performance of your API.
  • Cost for High Throughput
    While cost-effective for low to moderate usage, the costs can escalate with high throughput and large data transfers.
  • Debugging Issues
    Diagnosis can be complicated due to the multi-tenant nature of the service and the need to dive into multiple AWS logs and services.
  • Limited Customization
    There might be constraints regarding customizations and fine-tuning your APIs compared to self-hosting solutions.
  • Vendor Lock-in
    Dependence on AWS infrastructure can lead to vendor lock-in, making it challenging to migrate to other cloud providers or solutions.

Analysis of Amazon API Gateway

Overall verdict

  • Amazon API Gateway is considered a good choice for businesses and developers who are looking for a reliable and scalable API management solution, especially if they are already using other AWS services.

Why this product is good

  • Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. It is highly scalable, offers robust features like automatic security patches, supports multiple authentication mechanisms, and integrates seamlessly with other AWS services. Additionally, it provides detailed monitoring and logging, which facilitates effective API management.

Recommended for

  • Developers building serverless applications on AWS, particularly with AWS Lambda.
  • Organizations that require secure, scalable, and highly available APIs.
  • Businesses seeking seamless integrations within the AWS ecosystem.
  • Teams that need detailed monitoring, logging, and security features for their APIs.

Apache Parquet videos

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Amazon API Gateway videos

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Building APIs with Amazon API Gateway

More videos:

  • Review - Create API using AWS API Gateway service - Amazon API Gateway p1

Category Popularity

0-100% (relative to Apache Parquet and Amazon API Gateway)

Apache Parquet

Amazon API Gateway

Databases
100 100%
Databases
0% 0
API Tools
0 0%
API Tools
100% 100
Big Data
100 100%
Big Data
0% 0
APIs
0 0%
APIs
100% 100

User comments

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Social recommendations and mentions

Based on our record, Amazon API Gateway should be more popular than Apache Parquet. It has been mentiond 108 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 Parquet mentions (24)

  • How to Pitch Your Boss to Adopt Apache Iceberg?
    Iceberg decouples storage from compute. That means your data isn’t trapped inside one proprietary system. Instead, it lives in open file formats (like Apache Parquet) and is managed by an open, vendor-neutral metadata layer (Apache Iceberg). - Source: dev.to / 2 months ago
  • Processing data with “Data Prep Kit” (part 2)
    Data prep kit github repository: https://github.com/data-prep-kit/data-prep-kit?tab=readme-ov-file Quick start guide: https://github.com/data-prep-kit/data-prep-kit/blob/dev/doc/quick-start/contribute-your-own-transform.md Provided samples and examples: https://github.com/data-prep-kit/data-prep-kit/tree/dev/examples Parquet: https://parquet.apache.org/. - Source: dev.to / 2 months ago
  • 🔬Public docker images Trivy scans as duckdb datas on Kaggle
    Deliver nice ready-to-use data as duckdb, parquet and csv. - Source: dev.to / 3 months ago
  • Introducing Promptwright: Synthetic Dataset Generation with Local LLMs
    Push the dataset to hugging face in parquet format. - Source: dev.to / 8 months ago
  • Shades of Open Source - Understanding The Many Meanings of "Open"
    It's this kind of certainty that underscores the vital role of the Apache Software Foundation (ASF). Many first encounter Apache through its pioneering project, the open-source web server framework that remains ubiquitous in web operations today. The ASF was initially created to hold the intellectual property and assets of the Apache project, and it has since evolved into a cornerstone for open-source projects... - Source: dev.to / about 1 year ago
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Amazon API Gateway mentions (108)

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What are some alternatives?

When comparing Apache Parquet and Amazon API Gateway, you can also consider the following products

Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.

AWS Lambda - Automatic, event-driven compute service

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

Postman - The Collaboration Platform for API Development

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

Apigee - Intelligent and complete API platform

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