Software Alternatives, Accelerators & Startups

Algolia VS Apache Spark

Compare Algolia VS Apache Spark and see what are their differences

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Algolia logo Algolia

Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

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.
  • Algolia Landing page
    Landing page //
    2023-10-19
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Algolia

$ Details
Release Date
2012 January
Startup details
Country
United States
State
California
Founder(s)
Julien Lemoine
Employees
250 - 499

Algolia features and specs

  • Speed
    Algolia is known for its incredibly fast search results. It can return search results in milliseconds, enhancing user experience on any application.
  • Ease of Integration
    Algolia provides easy-to-use APIs and extensive documentation, making it straightforward to integrate into various technologies and platforms.
  • Customizable Relevance
    With Algolia, you can fine-tune the relevance of your search results using an extensive set of customizable settings and ranking algorithms.
  • Scalability
    Algolia can handle large amounts of data and user queries, ensuring scalable performance as your application grows.
  • Real-time Indexing
    Changes to your indexed data are reflected in real-time, ensuring that the search results are always up-to-date.
  • Faceted Search and Filtering
    Algolia provides robust faceted search capabilities, allowing users to filter search results dynamically based on various criteria.
  • Multilingual Support
    Algolia supports search queries in multiple languages, making it feasible for applications with a global user base.
  • Advanced Analytics
    Algolia offers detailed analytics and insights, helping you to better understand how users interact with your search feature and to improve it continuously.

Possible disadvantages of Algolia

  • Cost
    Algolia can be quite expensive, especially for small businesses and startups, as pricing is based on the number of operations and indexing.
  • Complexity in Advanced Features
    While the basic setup is straightforward, implementing advanced features and fine-tuning relevance can require significant technical expertise.
  • Limited Free Tier
    The free tier of Algolia is limited in terms of indexing and operations, which may not be sufficient for even moderately-sized projects.
  • Data Hosting Regulations
    Algolia's cloud-based hosting means that data may not always reside in the same country as your user base, which could be a concern for businesses needing to comply with specific data sovereignty regulations.
  • Dependence on Third-party Service
    Reliance on a third-party service for crucial functionality like search means that your application could be affected by downtime or service changes at Algolia.
  • Customization Requires Coding
    Any significant customization or specific use-case implementation requires coding effort, which could be a barrier for non-technical users.

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Algolia videos

Discover Algolia #1 - When To Use (and not to use) Algolia

More videos:

  • Review - Algolia Search – The fastest prestashop module
  • Review - What is Algolia?

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 Algolia and Apache Spark)
Custom Search Engine
100 100%
0% 0
Databases
0 0%
100% 100
Custom Search
100 100%
0% 0
Big Data
0 0%
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 Algolia and Apache Spark

Algolia Reviews

Top 9 Best WordPress Search Plugins To Improve Default Searches
This should allow a sufficient number of searches for many websites, so it’s worth checking out. Be sure to install Algolia’s official WordPress plugin to integrate it into your website.
Source: winningwp.com
4 Leading Enterprise Search Software to Look For in 2022
Algolia is a SaaS-based enterprise search software using RESTful API for websites and applications. Search Algolia API provides high performance and less than 10 ms of data response on average.
Top 10 Site Search Software Tools & Plugins for 2022
Algolia is a powerful search API that comes with a full-featured search engine. The lightning-fast search engine is typo-tolerant and language-aware, which helps to improve search relevance. It’s highly customizable so you can create unique search experiences for your customers.
Best Elasticsearch alternatives for search
Algolia is your standard choice of the Elasticsearch alternatives, having shot to popularity thanks to their low latency search and easy to implement prebuilt component library, Algolia Instant Search.
Source: relevance.ai
5 Open-Source Search Engines For your Website
Typesense is a fast, typo-tolerant search engine for building delightful search experiences. It claims that it is an Easier-to-Use ElasticSearch Alternative & an Open Source Algolia Alternative.
Source: vishnuch.tech

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 seems to be a lot more popular than Algolia. While we know about 70 links to Apache Spark, we've tracked only 3 mentions of Algolia. 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.

Algolia mentions (3)

Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 17 days ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / 19 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / about 2 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 2 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
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What are some alternatives?

When comparing Algolia and Apache Spark, you can also consider the following products

ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.

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

Typesense - Typo tolerant, delightfully simple, open source search 🔍

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

Apache Solr - Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.