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KeyDB VS Apache Arrow

Compare KeyDB VS Apache Arrow and see what are their differences

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KeyDB logo KeyDB

KeyDB is fast NoSQL database with full compatibility for Redis APIs, clients, and modules.

Apache Arrow logo Apache Arrow

Apache Arrow is a cross-language development platform for in-memory data.
  • KeyDB Landing page
    Landing page //
    2022-06-19
  • Apache Arrow Landing page
    Landing page //
    2021-10-03

KeyDB features and specs

  • High Performance
    KeyDB offers superior performance over Redis by allowing multi-threading, which utilizes multiple CPU cores efficiently, leading to significant improvements in throughput and latency.
  • Redis Compatibility
    KeyDB is fully compatible with Redis, meaning users can easily switch between Redis and KeyDB without needing to change their existing code or data structures.
  • Active Replication
    It supports multi-primary (active-active) replication, enabling all replicas to accept writes without worrying about conflicts, which increases availability and resilience.
  • Built-in TLS
    KeyDB includes built-in TLS support which enhances security by allowing data encryption in transit, a feature that requires third-party solutions in some Redis setups.
  • Persistence Options
    KeyDB supports both RDB snapshotting and AOF logging, offering flexible persistence strategies to balance between performance and durability.

Possible disadvantages of KeyDB

  • Community Size
    KeyDB, while gaining popularity, has a smaller community compared to Redis, which can lead to less community support and fewer third-party tools or extensions.
  • Maturity
    As a relatively newer project compared to Redis, KeyDB may lack the same level of proven stability and maturity, making it a potentially riskier choice for critical applications.
  • Documentation and Resources
    While KeyDB has extensive documentation, it might not be as comprehensive or complete as Redis, potentially leading to longer project integration times.
  • Potential Compatibility Issues
    Although KeyDB is compatible with Redis, advanced Redis features or unusual configurations might face compatibility issues during migration.
  • Less Architectural Simplicity
    The added complexity of multi-threading and active-active replication modes can increase the operational overhead compared to Redis's simpler single-threaded, master-slave architecture.

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.

KeyDB videos

+ Add

KeyDB on FLASH (Redis Compatible)

More videos:

  • Demo - Simple Demo of KeyDB on Flash in under 7 minutes (Drop in Redis Alternative)

Apache Arrow videos

+ Add

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 KeyDB and Apache Arrow)

KeyDB

Apache Arrow

Databases
48 48%
Databases
52% 52
Key-Value Database
100 100%
Key-Value Database
0% 0
NoSQL Databases
60 60%
NoSQL Databases
40% 40
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using KeyDB and Apache Arrow. For example, how are they different and which one is better?
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Reviews

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

KeyDB Reviews

Redis vs. KeyDB vs. Dragonfly vs. Skytable | Hacker News
2. KeyDB: The second is KeyDB. IIRC, I saw it in a blog post which said that it is a "multithreaded fork of Redis that is 5X faster"[1]. I really liked the idea because I was previously running several instances of Redis on the same node and proxying them like a "single-node cluster." Why? To increase CPU utilization. A single KeyDB instance could replace the unwanted...
Source: news.ycombinator.com
Comparing the new Redis6 multithreaded I/O to Elasticache & KeyDB
Because of KeyDB’s multithreading and performance gains, we typically need a much larger benchmark machine than the one KeyDB is running on. We have found that a 32 core m5.8xlarge is needed to produce enough throughput with memtier. This supports throughput for up to a 16 core KeyDB instance (medium to 4xlarge)
Source: docs.keydb.dev
KeyDB: A Multithreaded Redis Fork | Hacker News
"KeyDB works by running the normal Redis event loop on multiple threads. Network IO, and query parsing are done concurrently. Each connection is assigned a thread on accept(). Access to the core hash table is guarded by spinlock. Because the hashtable access is extremely fast this lock has low contention. Transactions hold the lock for the duration of the EXEC command....
Source: news.ycombinator.com

Apache Arrow Reviews

We have no reviews of Apache Arrow yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Arrow should be more popular than KeyDB. It has been mentiond 38 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.

KeyDB mentions (10)

  • Redis
    These facts only hold when the size of your payload and the number of connections remain relatively small. This easily jumps out the window with ever-increasing load parameters. The threshold is, unfortunately, rather low at a high number of connections and increased payload sizes. Modern large-scale micro-services will easily have over 100 running instances at medium scale. And since most instances employ some... - Source: dev.to / 3 months ago
  • Introducing LMS Moodle Operator
    The LMS Moodle Operator serves as a meta-operator, orchestrating the deployment and management of Moodle instances in Kubernetes. It handles the entire stack required to run Moodle, including components like Postgres, Keydb, NFS-Ganesha, and Moodle itself. Each of these components has its own Kubernetes Operator, ensuring seamless integration and management. - Source: dev.to / about 1 year ago
  • Dragonfly Is Production Ready (and we raised $21M)
    Congrats on the funding and getting production ready, it's good that KeyDB (and Redis) get some competition. https://docs.keydb.dev/ Open question, how does Dragonfly differ from KeyDB? - Source: Hacker News / about 2 years ago
  • I deleted 78% of my Redis container and it still works
    See: Distroless images[0] This is one of the huge benefits of recent systems languages like go and rust -- they compile to single binaries so you can use things like scatch[1] containers. You may have to fiddle with gnu libc/musl libc (usually when getaddrinfo is involved/dns etc), but once you're done with it, packaging is so easy. Even languages like Node (IMO the most progressive of the scripting languages)... - Source: Hacker News / almost 3 years ago
  • Dragonflydb – A modern replacement for Redis and Memcached
    Interesting project. Very similar to KeyDB [1] which also developed a multi-threaded scale-up approach to Redis. It's since been acquired by Snapchat. There's also Aerospike [2] which has developed a lot around low-latency performance. 1. https://docs.keydb.dev/ 2. https://aerospike.com/. - Source: Hacker News / almost 3 years ago
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Apache Arrow mentions (38)

  • 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 / 5 months 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 / 6 months ago
  • Kotlin DataFrame ❤️ Arrow
    Kotlin DataFrame v0.14 comes with improvements for reading Apache Arrow format, especially loading a DataFrame from any ArrowReader. This improvement can be used to easily load results from analytical databases (such as DuckDB, ClickHouse) directly into Kotlin DataFrame. - Source: dev.to / about 1 year 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 / 11 months ago
  • Arrow Flight SQL in Apache Doris for 10X faster data transfer
    Apache Doris 2.1 has a data transmission channel built on Arrow Flight SQL. (Apache Arrow is a software development platform designed for high data movement efficiency across systems and languages, and the Arrow format aims for high-performance, lossless data exchange.) It allows high-speed, large-scale data reading from Doris via SQL in various mainstream programming languages. For target clients that also... - Source: dev.to / 12 months ago
View more

What are some alternatives?

When comparing KeyDB and Apache Arrow, 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.

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 Ignite - high-performance, integrated and distributed in-memory platform for computing and transacting on...

memcached - High-performance, distributed memory object caching system

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

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