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Couchbase

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Couchbase vs Realm: What are the differences?

What is Couchbase? Document-Oriented NoSQL Database. 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.

What is Realm? Realm makes it easy to build reactive apps, realtime collaborative features, and offline-first experiences. The Realm Mobile Platform is a next-generation data layer for applications. Realm is reactive, concurrent, and lightweight, allowing you to work with live, native objects.

Couchbase can be classified as a tool in the "Databases" category, while Realm is grouped under "Mobile Database".

Some of the features offered by Couchbase are:

  • JSON document database
  • N1QL (SQL-like query language)
  • Secondary Indexing

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

  • Feels like Home - Realm’s data structures look like the Objects and Arrays of your language, but provide additional features such as: querying, relationships & graphs, thread safety, and more.
  • Memory-Efficient - Realm is not built on SQLite. Instead, a custom C++ core is used to provide memory-efficient access to your data by using Realm objects, which usually consume less RAM than native objects.
  • F-F-Fast! - Realm offers extraordinary performance compared to SQLite and other persistence solutions.

"Flexible data model, easy scalability, extremely fast" is the primary reason why developers consider Couchbase over the competitors, whereas "Good" was stated as the key factor in picking Realm.

Realm is an open source tool with 13.3K GitHub stars and 1.73K GitHub forks. Here's a link to Realm's open source repository on GitHub.

Geefu, Vestiaire Collective, and opening.io are some of the popular companies that use Couchbase, whereas Realm is used by SocialCops, Patreon, and Wongnai. Couchbase has a broader approval, being mentioned in 45 company stacks & 21 developers stacks; compared to Realm, which is listed in 39 company stacks and 5 developer stacks.

Advice on Couchbase and Realm
Needs advice
on
CouchbaseCouchbase
and
MongoDBMongoDB

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

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Replies (3)
Petr Havlicek
Freelancer at havlicekpetr.cz · | 12 upvotes · 110.6K views
Recommends
MongoDBMongoDB

I prefer MongoDB due to own experience with migration of old archive of pdf and meta-data to a new “archive”. The biggest advantage is speed of filters output - a new archive is way faster and reliable then the old one - but also the the easy programming of MongoDB with many code snippets and examples available. I have no personal experience so far with Couchbase. From the architecture point of view both options are OK - go for the one you like.

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Ivan Begtin
Director - NGO "Informational Culture" / Ambassador - OKFN Russia at Infoculture · | 7 upvotes · 110.7K views
Recommends
ArangoDBArangoDB

I would like to suggest MongoDB or ArangoDB (can't choose both, so ArangoDB). MongoDB is more mature, but ArangoDB is more interesting if you will need to bring graph database ideas to solution. For example if some data or some documents are interlinked, then probably ArangoDB is a best solution.

To process tables we used Abbyy software stack. It's great on table extraction.

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OtkudznamDamir Radinović-Lukić
Recommends
LinuxLinux

If you can select text with mouse drag in PDF. Use pdftotext it is fast! You can install it on server with command "apt-get install poppler-utils". Use it like "pdftotext -layout /path-to-your-file". In same folder it will make text file with line by line content. There is few classes on git stacks that you can use, also.

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Decisions about Couchbase and Realm
Gabriel Pa

After using couchbase for over 4 years, we migrated to MongoDB and that was the best decision ever! I'm very disappointed with Couchbase's technical performance. Even though we received enterprise support and were a listed Couchbase Partner, the experience was horrible. With every contact, the sales team was trying to get me on a $7k+ license for access to features all other open source NoSQL databases get for free.

Here's why you should not use Couchbase

Full-text search Queries The full-text search often returns a different number of results if you run the same query multiple types

N1QL queries Configuring the indexes correctly is next to impossible. It's poorly documented and nobody seems to know what to do, even the Couchbase support engineers have no clue what they are doing.

Community support I posted several problems on the forum and I never once received a useful answer

Enterprise support It's very expensive. $7k+. The team constantly tried to get me to buy even though the community edition wasn't working great

Autonomous Operator It's actually just a poorly configured Kubernetes role that no matter what I did, I couldn't get it to work. The support team was useless. Same lack of documentation. If you do get it to work, you need 6 servers at least to meet their minimum requirements.

Couchbase cloud Typical for Couchbase, the user experience is awful and I could never get it to work.

Minimum requirements The minimum requirements in production are 6 servers. On AWS the calculated monthly cost would be ~$600. We achieved better performance using a $16 MongoDB instance on the Mongo Atlas Cloud

writing queries is a nightmare While N1QL is similar to SQL and it's easier to write because of the familiarity, that isn't entirely true. The "smart index" that Couchbase advertises is not smart at all. Creating an index with 5 fields, and only using 4 of them won't result in Couchbase using the same index, so you have to create a new one.

Couchbase UI The UI that comes with every database deployment is full of bugs, barely functional and the developer experience is poor. When I asked Couchbase about it, they basically said they don't care because real developers use SQL directly from code

Consumes too much RAM Couchbase is shipped with a smaller Memcached instance to handle the in-memory cache. Memcached ends up using 8 GB of RAM for 5000 documents! I'm not kidding! We had less than 5000 docs on a Couchbase instance and less than 20 indexes and RAM consumption was always over 8 GB

Memory allocations are useless I asked the Couchbase team a question: If a bucket has 1 GB allocated, what happens when I have more than 1GB stored? Does it overflow? Does it cache somewhere? Do I get an error? I always received the same answer: If you buy the Couchbase enterprise then we can guide you.

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Gabriel Pa

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

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Pros of Couchbase
Pros of Realm
  • 18
    High performance
  • 18
    Flexible data model, easy scalability, extremely fast
  • 9
    Mobile app support
  • 7
    You can query it with Ansi-92 SQL
  • 6
    All nodes can be read/write
  • 5
    Open source, community and enterprise editions
  • 5
    Both a key-value store and document (JSON) db
  • 5
    Equal nodes in cluster, allowing fast, flexible changes
  • 4
    Local cache capability
  • 4
    Automatic configuration of sharding
  • 3
    Cross data center replication
  • 3
    Elasticsearch connector
  • 3
    Easy setup
  • 3
    Web based management, query and monitoring panel
  • 3
    Linearly scalable, useful to large number of tps
  • 3
    Easy cluster administration
  • 3
    SDKs in popular programming languages
  • 2
    Map reduce views
  • 2
    DBaaS available
  • 2
    NoSQL
  • 1
    FTS + SQL together
  • 1
    Buckets, Scopes, Collections & Documents
  • 7
    Good
  • 3
    Elegant API
  • 3
    Cloud Syncing
  • 2
    React Native Support
  • 1
    Strong Adoption Growth

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Cons of Couchbase
Cons of Realm
  • 3
    Terrible query language
  • 1
    No offline support for web till now

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What is 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.

What is Realm?

The Realm Mobile Platform is a next-generation data layer for applications. Realm is reactive, concurrent, and lightweight, allowing you to work with live, native objects.

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What companies use Couchbase?
What companies use Realm?
See which teams inside your own company are using Couchbase or Realm.
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What tools integrate with Couchbase?
What tools integrate with Realm?

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What are some alternatives to Couchbase and Realm?
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.
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.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
HBase
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
See all alternatives