Software Alternatives & Reviews

Aerospike VS Apache Spark

Compare Aerospike VS Apache Spark and see what are their differences

Aerospike logo Aerospike

Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.

Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
  • Aerospike Landing page
    Landing page //
    2023-09-16
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Aerospike videos

Aerospike Demo of Aggregation Querying

Apache Spark videos

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Category Popularity

0-100% (relative to Aerospike and Apache Spark)
Databases
30 30%
70% 70
NoSQL Databases
100 100%
0% 0
Big Data
0 0%
100% 100
Key-Value Database
100 100%
0% 0

User comments

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Reviews

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

Aerospike Reviews

7 Best NoSQL APIs
The last piece of the puzzle when it comes to the attraction of Aerospike is its hybrid memory architecture. Aerospike takes an approach to storing data uniquely. It stores the index only in memory while the data persists in a solid state drive (SSD). While the magic in output lies deeper in the architecture, clients receive sub-millisecond latency read times at a throughput...
When to use Aerospike vs Redis | Aerospike
Need for strong data consistency If companies are building mission-critical applications where data consistency is a must, then Redis is not likely the right choice. Redis has not passed the Jepsen test for strong consistency (whereas Aerospike has). Redis supports eventual consistency, which can result in stale reads and even data loss under certain circumstances. Redis has...

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Aerospike. It has been mentiond 56 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.

Aerospike mentions (8)

  • Aerospike Driver for LINQPad
    Aerospike for LINQPad 7 is a data context dynamic driver for interactively querying and updating an Aerospike database using “LINQPad”. The driver is free. For more information go to this blog post. You can directly download the driver from the LINQPad NuGet manager. Source: about 1 year ago
  • Using In-Memory Databases in Data Science
    Aerospike is a real-time cloud structured platform with good performance capabilities. This IMDB platform allows enterprises to perform their operations in real time through the hybrid memory and parallelism model. - Source: dev.to / over 1 year ago
  • Block and Filesystem side-by-side with K8s and Aerospike
    Block storage stores a sequence of bytes in a fixed size block (page) on a storage device. Each block has a unique hash that references the address location of the specified block. Unlike a filesystem, block storage doesn't have the associated metadata such as format-type, owner, date, etc. Also, block storage doesn’t use the conventional storage paths to access data like a filesystem file. This reduction in... - Source: dev.to / over 1 year ago
  • Aerospike & IoT using MQTT
    This example shows how the Aerospike database can be easily and scalably used to store industrial time series data made available by the MQTT ecosystem. Aerospike plus its Community Time Series Client streamlines the storage and retrieval of the data, supporting the ability to both write and read millions of data points per second if required. - Source: dev.to / over 1 year ago
  • Building Large-Scale Real-Time JSON Applications
    Real-time large-scale JSON applications need reliably fast access to data, high ingest rates, powerful queries, rich document functionality, scalability with no practical limit, always-on operation, and integration with streaming and analytical platforms. They need all this at low cost. The Aerospike Real-time Data Platform provides all this functionality, making it a good choice for building such applications.... - Source: dev.to / over 1 year ago
View more

Apache Spark mentions (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
View more

What are some alternatives?

When comparing Aerospike and Apache Spark, 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.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

memcached - High-performance, distributed memory object caching system

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

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

Hadoop - Open-source software for reliable, scalable, distributed computing