Elasticsearch vs mongodb reddit. MongoDB is an open-source NoSQL database management program, which can be used to manage large amounts of data in a distributed architecture. I'd like to know if there's any thing elasticsearch can't do before migrating to it. May 18, 2021 · Elasticsearch is built for search and provides advanced data indexing capabilities. It is implemented in Java programming language and supports all operating systems having java virtual machines (J. Dec 4, 2025 · A common question arises: *Can Elasticsearch replace MongoDB as a primary data store for large-scale, real-time search use cases? Or is pairing MongoDB with Elasticsearch the better approach?* This blog dives deep into the strengths, limitations, and ideal use cases of both tools to help you decide. For data analysis, it operates alongside Kibana, and Logstash to form the ELK stack. Have built-in Embedding models: ELSER. It is the main component of Elastic Stack, which is a open source application for data analysis and visualization. Elasticsearch : Elasticsearch is a distributed search and analytics engine. For all top_k values, ES is performing much faster. 2 - Searching across multiple-collections 3 - Search auto-complete 4 - Search suggestions How would you compare ElasticSearch vs MongoDB Atlas. It has high scalability Feb 28, 2026 · In this blog, we will explore Elasticsearch vs MongoDB, helping you decide to select the best database solution. I've heard many things about mongo and I'd like to learn more about it. If you just take a look at the community version of both, the backup option of elasticsearch is definitely better. Hello, We're using MongoDB Atlas, and we need to use a search engine for the following functionalities: 1 - We're seeking the best full text-search across multiple collections, with suggestions and auto-complete functionality. mongoDB vs elasticsearch: some use cases examples? Hi all, I am new to the world of databases. You might try that. Also for top_k = 5, ES retrieved correct document link 37% times accurately than ChromaDB. Hybrid search with text+vector Security Cons: Doesn't support quantization, which may be too exhaustive when Jan 4, 2024 · MongoDB’s document-oriented model and scalability make it an excellent choice for applications with varied data structures, while Elasticsearch’s focus on search and distributed nature caters The top benchmarks section will focus on time-series databases that are fast, provide time-series joins, time window aggregations and data compression, rather than pull in more general solutions. We would like to show you a description here but the site won’t allow us. MongoDB is an open-source NoSQL database management program, which can be used to manage large amounts of data in a distributed architecture Jul 15, 2025 · 1. M). An organization might use one of them or all of them for different types of data and to support different access aids. When it comes to noSQL, I'm pretty familiar with elasticsearch which is part of my job. But one of my colleague suggested using Elastic Search for they mentioned it is much faster and accurate. Many thanks for your time Jan 4, 2024 · MongoDB’s document-oriented model and scalability make it an excellent choice for applications with varied data structures, while Elasticsearch’s focus on search and distributed nature caters May 18, 2021 · Elasticsearch is built for search and provides advanced data indexing capabilities. Conclusion Both Elasticsearch and MongoDB are powerful in their own right. 5 days ago · The S&P 500 was on track for double-digit earnings growth, with more than half of companies having reported Q4 results so far. Is anything wrong or supplemental? Thank you! Pros: It's an Elastic product, meaning high SLA and needless to buy other products when doing business with Elastic. But I just start to learn and use elasticsearch now. See our blog post for the data trends and events of 2024. Can I replace mongodb with elasticsearch. MongoDB is a document key value store (nosql). Elasticsearch is a text database that essentially inverts the index of text you feed it. V. Aug 28, 2024 · Elasticsearch is primarily a search engine optimized for fast, complex search queries, especially text searches, and is often used for log and event data analysis. All are databases, but serve very different uses. Reply reply phirestalker • I'm comparing Elastic vs other pure vector databases vs Mongodb/redis offerings. Hybrid search with text+vector Security Cons: Doesn't support quantization, which may be too exhaustive when I'm comparing Elastic vs other pure vector databases vs Mongodb/redis offerings. MongoDB, on the other hand, is a general-purpose, document-oriented database that excels in storing and retrieving structured and semi-structured data. I played around with dynamoDB a tiny bit too, but that's as far as my experience goes. One of the things is transaction. It's not a benchmark, but we tested to see We provide native integration for MongoDB analytics and ElasticSearch analytics, eliminating the need for an ETL tool and delivering a high-level intuitive UI, allowing users to generate queries and maneuver the data with a simple drag-and-drop functionality. Updated 2nd January 2025 Various open-source databases got closer to top performance in clickbench. It is open source and can be used for all types of data. OpenSearch is the fork from ElasticSearch before they went opensource-ish-but-not-for-amazon (tm). So I did my own testing and found that for top_k=5, ES is 100% faster than ChromaDB. osjhwf ypv stpus elviu jyqd avalx smwu botu ghya bpbd