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Redis ™ VS Apache ORC

Compare Redis VS Apache ORC and see what are their differences

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Redis logo Redis

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

Apache ORC logo Apache ORC

Apache ORC is a columnar storage for Hadoop workloads.
  • Redis Landing page
    Landing page //
    2022-10-19

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.

  • Apache ORC Landing page
    Landing page //
    2022-09-18

Redis features and specs

  • Performance
    Redis is an in-memory data store, which allows it to provide extremely fast read and write operations. This makes it ideal for applications requiring real-time interactions.
  • Data Structures
    Redis offers a variety of data structures, such as strings, hashes, lists, sets, and sorted sets. This flexibility helps developers manage data more efficiently in different scenarios.
  • Scalability
    Redis supports horizontal scalability with features like clustering and partitioning, allowing for easy scaling as your application grows.
  • Persistence
    Though primarily an in-memory store, Redis provides options for data persistence, such as RDB snapshots and AOF logs, enabling data durability across reboots.
  • Pub/Sub Messaging
    Redis includes a built-in publish/subscribe messaging system, which can be used to implement real-time messaging and notifications.
  • Simple API
    Redis has a simple and intuitive API, which can speed up development time and make it easier to integrate Redis into various application stacks.
  • Atomic Operations
    Redis supports atomic operations on data structures, reducing the complexity of concurrent programming and making it easier to maintain data consistency.

Possible disadvantages of Redis

  • Memory Usage
    Being an in-memory data store, Redis can become expensive in terms of memory usage, especially when working with large datasets.
  • Data Persistence Limitations
    While Redis offers data persistence, it is not as robust as traditional databases. There can be data loss in certain configurations, such as when using asynchronous persistence methods.
  • Complexity in Scaling
    Although Redis supports clustering, setting up and managing a Redis cluster can be complex and may require significant DevOps expertise.
  • Single-threaded Nature
    Redis operates on a single-threaded event loop, which can become a bottleneck for certain workloads that could benefit from multi-threading.
  • Limited Query Capabilities
    Compared to traditional relational databases, Redis offers limited querying capabilities. Complex queries and joins are not supported natively.
  • License
    As of Redis 6 and higher, the Redis modules are under the Server Side Public License (SSPL), which may be restrictive for some use cases compared to more permissive open-source licenses.

Apache ORC features and specs

  • Efficient Compression
    ORC provides highly efficient compression, which reduces the storage footprint of data and enhances performance by decreasing I/O operations.
  • Columnar Storage
    The columnar storage format significantly improves read performance by allowing for selective access to necessary columns while ignoring others.
  • Predicate Pushdown
    ORC supports predicate pushdown, enabling the query engine to skip over non-relevant data, thus enhancing query performance.
  • Type Richness
    ORC supports complex types (like structs and maps), making it suitable for diverse data storage and query needs.
  • Schema Evolution
    It facilitates seamless schema evolution, allowing easier adjustments to the dataset over time without breaking existing queries.
  • Built-in Indexes
    Indexes such as bloom filters and min/max values are built-in, accelerating query processing by enabling quicker data lookup.

Possible disadvantages of Apache ORC

  • Complexity
    The intricacies of its features may introduce additional complexity in implementation and maintenance, potentially increasing the learning curve.
  • Write Performance
    While ORC is optimized for read-heavy workloads, its write performance can be less efficient compared to other formats like Parquet.
  • Compatibility
    ORC may not be as widely supported as other formats, limiting the choice of tools and environments that can leverage its full capabilities.
  • Compression Overhead
    The process of compressing and decompressing data can introduce a computational overhead, affecting performance in some scenarios.

Redis videos

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Improve your Redis developer experience with RedisInsight, Redis Labs

More videos:

  • Review - What is Redis? | Why and When to use Redis? | Tech Primers
  • Review - Redis Enterprise Overview with Yiftach Shoolman - Redis Labs
  • Review - Redis Labs "Why NoSQL is a Safe Bet"
  • Review - Redis system design | Distributed cache System design
  • Review - What is Redis and What Does It Do?
  • Review - Redis Sorted Sets Explained

Apache ORC videos

No Apache ORC videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Redis and Apache ORC)

Redis

Apache ORC

Databases
98 98%
Databases
2% 2
Big Data
0 0%
Big Data
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Data Dashboard
0 0%
Data Dashboard
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 Redis and Apache ORC

Redis Reviews

Redis Alternative for App Performance | Gigaspaces
Redis offers a RESTful API for accessing data stored within its in-memory technology data structures. This API provides a simple and efficient way to interact with Redis, enabling developers to leverage its capabilities seamlessly in their applications. Developers also need to manage the Redis cached data lifecycle, it’s the application responsibility to store the data &...
Source: www.gigaspaces.com
Are Free, Open-Source Message Queues Right For You?
A notable challenge with Redis Streams is that it doesn't natively support distributed, horizontal scaling. Also, while Redis is famous for its speed and simplicity, managing and scaling a Redis installation may be complex for some users, particularly for persistent data workloads.
Source: blog.iron.io
Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
1. Redis: I'll start with Redis which I'd like to call the "original" key/value store (after memcached) because it is the oldest and most widely used of all. Being a long-time follower of Redis, I do know it's single-threaded (and uses io-threads since 6.0) and hence it achieves lesser throughput than the other stores listed above which are multi-threaded, at least to some...
Source: news.ycombinator.com
Memcached vs Redis - More Different Than You Would Expect
Remember when I wrote about how Redis was using malloc to assign memory? I lied. While Redis did use malloc at some point, these days Redis actually uses jemalloc. The reason for this is that jemalloc, while having lower peak performance has lower memory fragmentation helping to solve the framented memory issues that Redis experiences.
Source: engineering.kablamo.com.au
Top 15 Kafka Alternatives Popular In 2021
Redis is a known, open-source, in-memory data structure store that offers different data structures like lists, strings, hashes, sets, bitmaps, streams, geospatial indexes, etc. It is best utilized as a cache, memory broker, and cache. It has optional durability and inbuilt replication potential. It offers a great deal of availability through Redis Sentinel and Redis Cluster.
Source: www.spec-india.com

Apache ORC Reviews

We have no reviews of Apache ORC yet.
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Social recommendations and mentions

Based on our record, Redis seems to be a lot more popular than Apache ORC. While we know about 226 links to Redis, we've tracked only 3 mentions of Apache ORC. 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.

Redis mentions (226)

  • Hacktoberfest 2025 with Ghostfolio
    The software is fully written in TypeScript and organized as an Nx workspace, utilizing the latest framework releases. The backend is based on NestJS in combination with PostgreSQL as a database together with Prisma and Redis for caching. The frontend is developed with Angular. - Source: dev.to / 6 days ago
  • Redis Explained: What It Is, Why You Need It, and How to Install It the Easy Way
    Here’s the thing: sometimes it’s not your database’s fault. What’s missing is a speed booster in your architecture: Redis. - Source: dev.to / 29 days ago
  • Real-Time Sync Alternatives: Vaultrice vs. localStorage, DIY, Firebase, Pusher
    This is the path of ultimate control. You spin up a Node.js server, add the socket.io library for WebSocket communication, and use a Redis instance to manage connection state and pub/sub messaging across multiple server instances. - Source: dev.to / about 1 month ago
  • Is Your Fraud Screening Process Ignoring Local Patterns?
    Your Database: This is your system's memory. It can be a fast in-memory store like Redis for temporary data (perfect for velocity checks) or a persistent relational database like PostgreSQL for long-term data (like blacklists). - Source: dev.to / about 1 month ago
  • Redis vs. Memcached: How to Choose Your NoSQL Champion
    Redis is also an in-memory system with exceptional performance. But unlike Memcached, Redis is known as a "data structure server." It doesn't just support simple key-value pairs; it offers a rich variety of complex data structures like Lists, Hashes, Sets, and Sorted Sets. - Source: dev.to / about 2 months ago
View more

Apache ORC mentions (3)

  • Java Serialization with Protocol Buffers
    The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / almost 3 years ago
  • AWS EMR Cost Optimization Guide
    Data formatting is another place to make gains. When dealing with huge amounts of data, finding the data you need can take up a significant amount of your compute time. Apache Parquet and Apache ORC are columnar data formats optimized for analytics that pre-aggregate metadata about columns. If your EMR queries column intensive data like sum, max, or count, you can see significant speed improvements by reformatting... - Source: dev.to / almost 4 years ago
  • Apache Hudi - The Streaming Data Lake Platform
    The following stack captures layers of software components that make up Hudi, with each layer depending on and drawing strength from the layer below. Typically, data lake users write data out once using an open file format like Apache Parquet/ORC stored on top of extremely scalable cloud storage or distributed file systems. Hudi provides a self-managing data plane to ingest, transform and manage this data, in a... - Source: dev.to / about 4 years ago

What are some alternatives?

When comparing Redis and Apache ORC, you can also consider the following products

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

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

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

BlueData - BlueData's software platform makes it easier, faster and more cost-effective for organizations to deploy Big Data infrastructure on-premises.

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