Cloudant vs Elasticsearch

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Cloudant
Cloudant

29
30
+ 1
20
Elasticsearch
Elasticsearch

8.5K
5.7K
+ 1
1.6K
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Cloudant vs Elasticsearch: What are the differences?

Cloudant: Distributed database-as-a-service (DBaaS) for web & mobile apps. Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own; Elasticsearch: Open Source, Distributed, RESTful Search Engine. Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Cloudant and Elasticsearch are primarily classified as "NoSQL Database as a Service" and "Search as a Service" tools respectively.

Some of the features offered by Cloudant are:

  • Managed- Cloudant's big data experts monitor your data 24/7 to ensure its high availability and safety.
  • Distributed Multi-Master Database- All read and write transactions can be synced across Cloudant's global data network without global locks, providing true high availability of your data.
  • Geo-load Balancing- To keep latency low, our geo-load balancing infrastructure routes requests to the copies of the data that are geographically closest to the requestor.

On the other hand, Elasticsearch provides the following key features:

  • Distributed and Highly Available Search Engine.
  • Multi Tenant with Multi Types.
  • Various set of APIs including RESTful

"JSON" is the top reason why over 8 developers like Cloudant, while over 310 developers mention "Powerful api" as the leading cause for choosing Elasticsearch.

Elasticsearch is an open source tool with 42.4K GitHub stars and 14.2K GitHub forks. Here's a link to Elasticsearch's open source repository on GitHub.

- No public GitHub repository available -

What is Cloudant?

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

What is Elasticsearch?

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
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    What are some alternatives to Cloudant and Elasticsearch?
    CouchDB
    Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
    Couchbase
    Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Amazon DynamoDB
    All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
    Cloud Firestore
    Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.
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    Decisions about Cloudant and Elasticsearch
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    How developers use Cloudant and Elasticsearch
    Avatar of imgur
    imgur uses ElasticsearchElasticsearch

    Elasticsearch is the engine that powers search on the site. From a high level perspective, it’s a Lucene wrapper that exposes Lucene’s features via a RESTful API. It handles the distribution of data and simplifies scaling, among other things.

    Given that we are on AWS, we use an AWS cloud plugin for Elasticsearch that makes it easy to work in the cloud. It allows us to add nodes without much hassle. It will take care of figuring out if a new node has joined the cluster, and, if so, Elasticsearch will proceed to move data to that new node. It works the same way when a node goes down. It will remove that node based on the AWS cluster configuration.

    Avatar of Instacart
    Instacart uses ElasticsearchElasticsearch

    The very first version of the search was just a Postgres database query. It wasn’t terribly efficient, and then at some point, we moved over to ElasticSearch, and then since then, Andrew just did a lot of work with it, so ElasticSearch is amazing, but out of the box, it doesn’t come configured with all the nice things that are there, but you spend a lot of time figuring out how to put it all together to add stemming, auto suggestions, all kinds of different things, like even spelling adjustments and tomato/tomatoes, that would return different results, so Andrew did a ton of work to make it really, really nice and build a very simple Ruby gem called SearchKick.

    Avatar of AngeloR
    AngeloR uses ElasticsearchElasticsearch

    We use ElasticSearch for

    • Session Logs
    • Analytics
    • Leaderboards

    We originally self managed the ElasticSearch clusters, but due to our small ops team size we opt to move things to managed AWS services where possible.

    The managed servers, however, do not allow us to manage our own backups and a restore actually requires us to open a support ticket with them. We ended up setting up our own nightly backup since we do per day indexes for the logs/analytics.

    Avatar of Brandon Adams
    Brandon Adams uses ElasticsearchElasticsearch

    Elasticsearch has good tooling and supports a large api that makes it ideal for denormalizing data. It has a simple to use aggregations api that tends to encompass most of what I need a BI tool to do, especially in the early going (when paired with Kibana). It's also handy when you just want to search some text.

    Avatar of Ana Phi Sancho
    Ana Phi Sancho uses ElasticsearchElasticsearch

    Self taught : acquired knowledge or skill on one's own initiative. Open Source Search & Analytics. -time search and analytics engine. Search engine based on Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

    Avatar of Aaron Buchanan
    Aaron Buchanan uses CloudantCloudant

    hosted couchdb

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