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Aerospike

199
283
+ 1
48
KeyDB

34
61
+ 1
5
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Aerospike vs KeyDB: What are the differences?

Introduction

Aerospike and KeyDB are both database management systems, designed to handle large-scale data storage and retrieval. While they share some similarities, there are also key differences that set them apart.

  1. Data Model: Aerospike uses a key-value data model, where data is stored and accessed using a unique key. On the other hand, KeyDB supports multiple data models including key-value, document, graph, and time series data, providing more flexibility in data representation.

  2. Architecture: Aerospike is a distributed NoSQL database, designed for high-performance and low-latency operations. It utilizes a single-threaded, shared-nothing architecture, where each node operates independently. In contrast, KeyDB is an in-memory database that utilizes a multi-threaded architecture to achieve better performance and concurrency.

  3. Scalability: Aerospike supports horizontal scalability through automatic data partitioning and distribution across multiple nodes. It allows for seamless scaling by adding more nodes to the cluster. KeyDB, on the other hand, is primarily focused on in-memory caching and does not provide built-in horizontal scalability features like data partitioning.

  4. Consistency Model: Aerospike offers strong consistency guarantees by default, ensuring that all nodes in the cluster have the most up-to-date data. KeyDB, however, sacrifices strict consistency in favor of better performance, providing eventual consistency instead. This means that there may be a temporary lag between updates propagating across the entire cluster.

  5. Durability: Aerospike provides configurable data durability options, allowing users to choose between different levels of durability and persistency. It supports synchronous and asynchronous replication for data redundancy. KeyDB, on the other hand, focuses more on in-memory caching and does not provide built-in durability features, making it suitable for use cases where durability is not a strict requirement.

  6. Ecosystem and Community Support: Aerospike has a larger and more established community, with extensive documentation, tutorials, and community-driven resources available. It also has integrations with popular frameworks and tools. KeyDB, being a relatively new database, has a smaller community and may have limited support and resources compared to Aerospike.

In summary, Aerospike and KeyDB differ in their data models, architecture, scalability options, consistency models, durability features, and ecosystem/community support.

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Pros of Aerospike
Pros of KeyDB
  • 16
    Ram and/or ssd persistence
  • 12
    Easy clustering support
  • 5
    Easy setup
  • 4
    Acid
  • 3
    Scale
  • 3
    Performance better than Redis
  • 3
    Petabyte Scale
  • 2
    Ease of use
  • 3
    Performance
  • 2
    Active Replication

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What is Aerospike?

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

What is KeyDB?

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

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What tools integrate with Aerospike?
What tools integrate with KeyDB?
What are some alternatives to Aerospike and KeyDB?
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Riak
Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Tarantool
It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications
See all alternatives