Aerospike vs Kdb+

Overview

Aerospike

Stacks200

Followers288

Votes48

GitHub Stars1.3K

Forks196

Kdb+

Stacks15

Followers17

Votes0

Aerospike vs Kdb+: What are the differences?

Data Model: Aerospike is a NoSQL database that uses a key-value data model, while Kdb+ is a high-performance database that utilizes a columnar data model specifically designed for time-series data.
Query Language: Aerospike supports its own query language called Aerospike Query Language (AQL), which is SQL-like, whereas Kdb+ uses its proprietary query language called q that is optimized for handling time-series and financial data efficiently.
Vertical Scalability: Aerospike can scale vertically by adding more resources to a single machine, allowing for increased performance, while Kdb+ is specifically designed for horizontal scalability across multiple machines for handling extensive datasets.
Use Cases: Aerospike is commonly used for real-time big data applications, like ad tech, whereas Kdb+ is widely utilized in the financial industry due to its high-speed data retrieval capabilities for time-series data analysis.
ACID Compliance: Aerospike is ACID (Atomicity, Consistency, Isolation, Durability) compliant, ensuring data integrity, while Kdb+ focuses more on speed and performance rather than strict ACID compliance.
Community Support: Aerospike has a larger community support with more extensive documentation and resources available, whereas Kdb+ has a smaller but dedicated community mainly focused on financial and time-series data analysis.

In Summary, key differences between Aerospike and Kdb+ include their data models, query languages, scalability options, use cases, ACID compliance, and community support.

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Detailed Comparison

Aerospike	Kdb+
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.	It is a column-based relational time-series database with in-memory abilities. The database is commonly used in high-frequency trading to store, analyze, process, and retrieve large data sets at high speed. kdb+ has the ability to handle billions of records and analyzes data within a database.
99% of reads/writes complete in under 1 millisecond.;Predictable low latency at high throughput – second to none. Read the YCSB Benchmark.;The secret sauce? A thousand things done right. Server code in ‘C’ (not Java or Erlang) precisely tuned to avoid context switching and memory copies. Highly parallelized multi-threaded, multi-core, multi-cpu, multi-SSD execution.;Indexes are always stored in RAM. Pure RAM mode is backed by spinning disks. In hybrid mode, individual tables are stored in either RAM or flash.	In-memory compute engine; Real-time streaming processor
Statistics
GitHub Stars 1.3K	GitHub Stars -
GitHub Forks 196	GitHub Forks -
Stacks 200	Stacks 15
Followers 288	Followers 17
Votes 48	Votes 0
Pros & Cons
Pros 16 Ram and/or ssd persistence 12 Easy clustering support 5 Easy setup 4 Acid 3 Performance better than Redis	No community feedback yet

What are some alternatives to Aerospike, Kdb+?

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.

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

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

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

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.

LokiJS

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

Related Comparisons

Aerospike vs Kdb+: What are the differences?

Data Model: Aerospike is a NoSQL database that uses a key-value data model, while Kdb+ is a high-performance database that utilizes a columnar data model specifically designed for time-series data.
Query Language: Aerospike supports its own query language called Aerospike Query Language (AQL), which is SQL-like, whereas Kdb+ uses its proprietary query language called q that is optimized for handling time-series and financial data efficiently.
Vertical Scalability: Aerospike can scale vertically by adding more resources to a single machine, allowing for increased performance, while Kdb+ is specifically designed for horizontal scalability across multiple machines for handling extensive datasets.
Use Cases: Aerospike is commonly used for real-time big data applications, like ad tech, whereas Kdb+ is widely utilized in the financial industry due to its high-speed data retrieval capabilities for time-series data analysis.
ACID Compliance: Aerospike is ACID (Atomicity, Consistency, Isolation, Durability) compliant, ensuring data integrity, while Kdb+ focuses more on speed and performance rather than strict ACID compliance.
Community Support: Aerospike has a larger community support with more extensive documentation and resources available, whereas Kdb+ has a smaller but dedicated community mainly focused on financial and time-series data analysis.

In Summary, key differences between Aerospike and Kdb+ include their data models, query languages, scalability options, use cases, ACID compliance, and community support.

Aerospike vs Kdb+

Overview