RavenDB vs RethinkDB

Overview

RethinkDB

Stacks292

Followers406

Votes307

GitHub Stars27.0K

Forks1.9K

RavenDB

Stacks79

Followers82

Votes9

GitHub Stars3.9K

Forks850

RavenDB vs RethinkDB: What are the differences?

Data Model: RavenDB is a document database, emphasizing flexibility and ease of use when working with JSON data, while RethinkDB focuses on a real-time feed architecture with changefeeds to push updates to applications instantly.
Query Language: RavenDB uses LINQ, a strongly typed querying language, making it more suitable for .NET developers, whereas RethinkDB uses ReQL, a functional language similar to JavaScript, offering more flexibility in querying.
Replication: RavenDB supports multi-master replication with conflict resolution, allowing for better scalability and fault tolerance in distributed environments, while RethinkDB provides built-in sharding for distribution but lacks multi-master replication.
ACID Compliance: RavenDB is ACID compliant, ensuring data consistency and reliability, which is crucial for transactional applications, whereas RethinkDB sacrifices some ACID properties for high availability and real-time capabilities.
Community and Support: RavenDB has a larger community and commercial support backing, making it more suitable for enterprise applications requiring guaranteed support and maintenance, while RethinkDB has a smaller community and limited commercial backing, potentially affecting long-term viability and support options.
Deployment Options: RavenDB can be deployed on-premises, in the cloud, or in a hybrid setup, offering flexibility in managing the database infrastructure, whereas RethinkDB is primarily designed for cloud-native applications, with optimized deployment options for cloud environments like Kubernetes.

In Summary, RavenDB and RethinkDB differ in their data model emphasis, query language, replication strategies, ACID compliance, community and support, and deployment options.

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CLI (Node.js)

Manual

Detailed Comparison

RethinkDB	RavenDB
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.	As a document database it remains true to the core principles of these type of storage mechanisms. Somehow it managed to combine the best of relational databases with that of document databases.
JSON data model and immediate consistency.;Distributed joins, subqueries, aggregation, atomic updates.;Secondary, compound, and arbitrarily computed indexes.;Hadoop-style map/reduce.;Friendly web and command-line administration tools.;Takes care of machine failures and network interrupts.;Multi-datacenter replication and failover.;Sharding and replication to multiple nodes.;Queries are automatically parallelized and distributed.;Lock-free operation via MVCC concurrency.	Multi-Platform; ACID Transactions
Statistics
GitHub Stars 27.0K	GitHub Stars 3.9K
GitHub Forks 1.9K	GitHub Forks 850
Stacks 292	Stacks 79
Followers 406	Followers 82
Votes 307	Votes 9
Pros & Cons
Pros 48 Powerful query language 46 Excellent dashboard 42 JSON 41 Distributed database 38 Open source	Pros 4 Embedded Library 3 Easy of use 2 NoSql
Integrations
Amazon EC2	Python Windows Java Ruby Linux

What are some alternatives to RethinkDB, RavenDB?

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

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

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

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 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

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.

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

RavenDB vs RethinkDB: What are the differences?

Data Model: RavenDB is a document database, emphasizing flexibility and ease of use when working with JSON data, while RethinkDB focuses on a real-time feed architecture with changefeeds to push updates to applications instantly.
Query Language: RavenDB uses LINQ, a strongly typed querying language, making it more suitable for .NET developers, whereas RethinkDB uses ReQL, a functional language similar to JavaScript, offering more flexibility in querying.
Replication: RavenDB supports multi-master replication with conflict resolution, allowing for better scalability and fault tolerance in distributed environments, while RethinkDB provides built-in sharding for distribution but lacks multi-master replication.
ACID Compliance: RavenDB is ACID compliant, ensuring data consistency and reliability, which is crucial for transactional applications, whereas RethinkDB sacrifices some ACID properties for high availability and real-time capabilities.
Community and Support: RavenDB has a larger community and commercial support backing, making it more suitable for enterprise applications requiring guaranteed support and maintenance, while RethinkDB has a smaller community and limited commercial backing, potentially affecting long-term viability and support options.
Deployment Options: RavenDB can be deployed on-premises, in the cloud, or in a hybrid setup, offering flexibility in managing the database infrastructure, whereas RethinkDB is primarily designed for cloud-native applications, with optimized deployment options for cloud environments like Kubernetes.

In Summary, RavenDB and RethinkDB differ in their data model emphasis, query language, replication strategies, ACID compliance, community and support, and deployment options.

RavenDB vs RethinkDB

Overview