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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. CouchDB vs ObjectBox

CouchDB vs ObjectBox

OverviewDecisionsComparisonAlternatives

Overview

CouchDB
CouchDB
Stacks529
Followers584
Votes139
GitHub Stars6.7K
Forks1.1K
ObjectBox
ObjectBox
Stacks9
Followers20
Votes0

CouchDB vs ObjectBox: What are the differences?

Introduction

CouchDB and ObjectBox are both database systems that differ in various aspects. Here are six key differences between them:

  1. Data Model: CouchDB is a document-oriented database, where data is stored as documents in JSON format. It allows flexible and dynamic schemas, making it suitable for handling unstructured or semi-structured data. On the other hand, ObjectBox is an object-oriented database that stores data as objects with strongly-typed classes. It requires a predefined schema before data can be stored.

  2. Querying: CouchDB uses a query language called MapReduce for querying the data. It allows complex queries, aggregations, and transformations on the documents. ObjectBox, on the other hand, uses a query API that is based on a builder pattern. It enables type-safe queries through the use of object properties and is optimized for high-performance queries.

  3. Replication and Sync: CouchDB has built-in support for replication and synchronization, allowing distributed databases to keep their data in sync with each other. It provides a robust and reliable mechanism for data replication. ObjectBox, on the other hand, lacks built-in replication and sync functionality. However, it offers integration into different synchronization frameworks or cloud services to achieve similar results.

  4. Scalability: CouchDB is designed to scale horizontally, meaning it can handle a large number of concurrent users and data by adding more servers to the cluster. It has built-in sharding and automatic partitioning to distribute the load across nodes. ObjectBox, on the other hand, is optimized for efficient device-side storage, primarily targeting mobile and edge use cases. While it can handle millions of objects efficiently on a single device, it is not designed for large-scale distributed systems.

  5. Storage: CouchDB stores data in a JSON-like format on disk, which provides human-readability but consumes more disk space. It is suitable for scenarios where data accessibility and query flexibility are prioritized. ObjectBox, on the other hand, uses a binary storage format optimized for efficient storage and retrieval, resulting in smaller storage requirements and faster data access.

  6. Language Support: CouchDB provides a RESTful HTTP API, making it accessible from any programming language that supports HTTP communication. It has a wide range of language bindings available. ObjectBox, on the other hand, has language-specific APIs that support different platforms such as Java, Kotlin, Swift, and Go. It provides strong language integration for efficient object handling and database operations.

Summary

In summary, CouchDB is a document-oriented database with flexible schemas, powerful querying capabilities, built-in replication, and scalability for distributed systems. ObjectBox, on the other hand, is an object-oriented database optimized for efficient device-side storage with a predefined schema, type-safe querying, and strong language integration.

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Advice on CouchDB, ObjectBox

Gabriel
Gabriel

CEO at Naologic

Jan 2, 2020

DecidedonCouchDBCouchDBCouchbaseCouchbaseMemcachedMemcached

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.

592k views592k
Comments

Detailed Comparison

CouchDB
CouchDB
ObjectBox
ObjectBox

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.

It is for developers who look for performance and ease of use. We are committed to providing you with the easiest APIs for you to keep your code short and maintainable. No SQL under the hood-Simply faster. Unlike other databases, it has been built from the ground up using key-value storage instead of column storage. The resulting performance is 10x faster than the leading alternative, we welcome you to try it yourself. It is fast regardless of the amount of data or operating system you are using.

Terrific single-node database; Clustered database ; HTTP/JSON; Offline first data sync
10x faster than any alternative; Reduces cloud costs up to 60%; Supports Linux, Windows, Mac/iOS, Android, Raspbian, etc. Embedded or Containerized; Develop applications that work on- and offline, independently from a constant Internet connection, providing an “always-on”-feeling; Accelerate time-to-market, save development and lifecycle costs, save precious developer time for tasks that bring value
Statistics
GitHub Stars
6.7K
GitHub Stars
-
GitHub Forks
1.1K
GitHub Forks
-
Stacks
529
Stacks
9
Followers
584
Followers
20
Votes
139
Votes
0
Pros & Cons
Pros
  • 43
    JSON
  • 30
    Open source
  • 18
    Highly available
  • 12
    Partition tolerant
  • 11
    Eventual consistency
No community feedback yet
Integrations
No integrations available
Linux
Linux
Android OS
Android OS
macOS
macOS
iOS
iOS
Windows
Windows
Raspbian
Raspbian

What are some alternatives to CouchDB, ObjectBox?

MongoDB

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.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

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.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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