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Meilisearch VS Apache Spark

Compare Meilisearch VS Apache Spark and see what are their differences

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Meilisearch logo Meilisearch

Ultra relevant, instant, and typo-tolerant full-text search API

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.
  • Meilisearch Landing page
    Landing page //
    2023-12-16

Meilisearch is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

  • Apache Spark Landing page
    Landing page //
    2021-12-31

Meilisearch features and specs

  • Speed
    Meilisearch is optimized for performance and provides very fast search capabilities, often with response times in milliseconds.
  • Relevance
    It offers advanced search features like typo tolerance, synonyms, and configurable ranking rules to ensure highly relevant search results.
  • Ease of Use
    Designed to be user-friendly with a straightforward RESTful API, making it easy to integrate and use.
  • Open Source
    Meilisearch is open source, allowing developers to inspect the code, contribute, and customize it to fit their own needs.
  • Language Support
    It supports multiple languages, ensuring effective full-text search capabilities in various linguistic contexts.
  • Lightweight
    Meilisearch is lightweight and can be deployed on modest hardware, making it suitable for small to medium-sized projects.
  • Real-time Indexing
    It offers real-time indexing, allowing the index to be updated without significant downtime or delay.

Possible disadvantages of Meilisearch

  • Maturity
    As a relatively young project, it may lack some advanced features and optimizations found in more established search solutions like Elasticsearch.
  • Ecosystem
    The ecosystem and community around Meilisearch are still growing, so you might find fewer plugins, extensions, and third-party tools compared to more mature solutions.
  • Scalability
    While suitable for small to medium projects, it might not be as scalable for very large datasets or highly complex queries compared to other search engines like Solr or Elasticsearch.
  • Complex Query Handling
    Meilisearch focuses on simplicity, which means it may lack some of the advanced query capabilities provided by more complex search engines.
  • Documentation
    Though improving, the documentation may not be as comprehensive as that of longer-established projects, which could lead to a steeper learning curve for some 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.

Meilisearch videos

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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 Meilisearch and Apache Spark)
Custom Search Engine
100 100%
0% 0
Databases
19 19%
81% 81
Search Engine
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 Meilisearch and Apache Spark

Meilisearch Reviews

5 Open-Source Search Engines For your Website
MeiliSearch is an open-source, blazingly fast and hyper-relevant search engine that will improve your search experience. It provides an extensive toolset for customization. It works out-of-the-box with a preset that easily answers the needs of most applications. Communication is done with a RESTful API because most developers are already familiar with its norms.
Source: vishnuch.tech
MeiliSearch: Zero-config alternative to Elasticsearch, made in Rust | Hacker News
"We send events to our Amplitude instance to be aware of the number of people who use MeiliSearch. We only send the platform on which the server runs once by day. No other information is sent. If you do not want us to send events, you can disable these analytics by using the MEILI_NO_ANALYTICS env variable."
Recommendations for Poor Man's ElasticSearch on AWS?
I'd second these two. I've been following them for quite some time. I even did an extensive research on which one I'd use, and I ended up with Typesense. I don't remember the specific reasoning though. Both seem quite good. MeiliSearch is written in Rust, which makes it more "hipsterish" ;)

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 Meilisearch. While we know about 70 links to Apache Spark, we've tracked only 4 mentions of Meilisearch. 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.

Meilisearch mentions (4)

  • Show HN: Cardstock- Free TCG Proxy Manager for Magic, Yugioh, & Pokemon
    This thing is amazing. Kamal gives me everything I could want (easy console access, easy shell access, a way to manage secrets, a way to see my logs, and letsencrypt support for DNS), all without a PaaS tax. The best part is the accessories feature: https://kamal-deploy.org/docs/commands/accessory/. I am running my main app with two accessories: Meilisearch(https://meilisearch.com) and OpenObserve... - Source: Hacker News / 4 months ago
  • Show HN: Hyvor Blogs – Multi-language blogging platform
    Meilisearch [https://meilisearch.com] for the search index. - Source: Hacker News / almost 2 years ago
  • Meilisearch, the Rust search engine, just raised $5M
    Meilisearch is an open-source, lightning-fast, and hyper-relevant search engine that fits effortlessly into your apps, websites, and workflow. You can find more info on our website https://meilisearch.com. Source: over 3 years ago
  • Search engines for website
    Algolia.com - new plans are very affordable Meilisearch.com - open source. Source: about 4 years ago

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 / 16 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 / 17 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 / about 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 Meilisearch and Apache Spark, you can also consider the following products

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

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

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.

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

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

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