Need advice about which tool to choose?Ask the StackShare community!

RethinkDB

292
387
+ 1
307
TimescaleDB

162
277
+ 1
41
Add tool

RethinkDB vs TimescaleDB: What are the differences?

RethinkDB: JSON. Scales to multiple machines with very little effort. Open source. 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; TimescaleDB: Scalable time-series database optimized for fast ingest and complex queries. Purpose-built as a PostgreSQL extension. TimescaleDB is the only open-source time-series database that natively supports full-SQL at scale, combining the power, reliability, and ease-of-use of a relational database with the scalability typically seen in NoSQL databases.

RethinkDB and TimescaleDB belong to "Databases" category of the tech stack.

Some of the features offered by RethinkDB are:

  • JSON data model and immediate consistency.
  • Distributed joins, subqueries, aggregation, atomic updates.
  • Secondary, compound, and arbitrarily computed indexes.

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

  • Packaged as a PostgreSQL extension
  • Full ANSI SQL
  • JOINs (e.g., across PostgreSQL tables)

RethinkDB and TimescaleDB are both open source tools. RethinkDB with 22.4K GitHub stars and 1.74K forks on GitHub appears to be more popular than TimescaleDB with 7.28K GitHub stars and 385 GitHub forks.

According to the StackShare community, RethinkDB has a broader approval, being mentioned in 37 company stacks & 25 developers stacks; compared to TimescaleDB, which is listed in 15 company stacks and 3 developer stacks.

Advice on RethinkDB and TimescaleDB
Umair Iftikhar
Technical Architect at ERP Studio · | 3 upvotes · 157.1K views
Needs advice
on
TimescaleDBTimescaleDBDruidDruid
and
CassandraCassandra

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

See more
Replies (1)
Recommends
MongoDBMongoDB

Hi Umair, Did you try MongoDB. We are using MongoDB on a production environment and collecting data from devices like your scenario. We have a MongoDB cluster with three replicas. Data from devices are being written to the master node and real-time dashboard UI is using the secondary nodes for read operations. With this setup write operations are not affected by read operations too.

See more
Needs advice
on
TimescaleDBTimescaleDBMongoDBMongoDB
and
InfluxDBInfluxDB

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

See more
Replies (3)
Yaron Lavi
Recommends
PostgreSQLPostgreSQL

We had a similar challenge. We started with DynamoDB, Timescale, and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us a We had a similar challenge. We started with DynamoDB, Timescale and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us better performance by far.

See more
Recommends
DruidDruid

Druid is amazing for this use case and is a cloud-native solution that can be deployed on any cloud infrastructure or on Kubernetes. - Easy to scale horizontally - Column Oriented Database - SQL to query data - Streaming and Batch Ingestion - Native search indexes It has feature to work as TimeSeriesDB, Datawarehouse, and has Time-optimized partitioning.

See more
Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 100.2K views
Recommends
Google BigQueryGoogle BigQuery

if you want to find a serverless solution with capability of a lot of storage and SQL kind of capability then google bigquery is the best solution for that.

See more
Decisions about RethinkDB and TimescaleDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 62.3K views

I chose TimescaleDB because to be the backend system of our production monitoring system. We needed to be able to keep track of multiple high cardinality dimensions.

The drawbacks of this decision are our monitoring system is a bit more ad hoc than it used to (New Relic Insights)

We are combining this with Grafana for display and Telegraf for data collection

See more
Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Pros of RethinkDB
Pros of TimescaleDB
  • 48
    Powerful query language
  • 46
    Excellent dashboard
  • 42
    JSON
  • 41
    Distributed database
  • 38
    Open source
  • 25
    Reactive
  • 16
    Atomic updates
  • 15
    Joins
  • 9
    MVCC concurrency
  • 9
    Hadoop-style map/reduce
  • 4
    Geospatial support
  • 4
    Real-time, open-source, scalable
  • 2
    Great Admin UI
  • 2
    A NoSQL DB with joins
  • 2
    YC Company
  • 2
    Fast, easily scalable, great customer support
  • 2
    Changefeeds: no polling needed to get updates
  • 8
    Open source
  • 7
    Easy Query Language
  • 6
    Time-series data analysis
  • 5
    Established postgresql API and support
  • 4
    Reliable
  • 2
    Paid support for automatic Retention Policy
  • 2
    Fast and scalable
  • 2
    Chunk-based compression
  • 2
    Postgres integration
  • 2
    High-performance
  • 1
    Case studies

Sign up to add or upvote prosMake informed product decisions

Cons of RethinkDB
Cons of TimescaleDB
    Be the first to leave a con
    • 4
      Licensing issues when running on managed databases

    Sign up to add or upvote consMake informed product decisions

    What is 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.

    What is TimescaleDB?

    TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use RethinkDB?
    What companies use TimescaleDB?
    See which teams inside your own company are using RethinkDB or TimescaleDB.
    Sign up for Private StackShareLearn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with RethinkDB?
    What tools integrate with TimescaleDB?

    Sign up to get full access to all the tool integrationsMake informed product decisions

    Blog Posts

    What are some alternatives to RethinkDB and TimescaleDB?
    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.
    CockroachDB
    It allows you to deploy a database on-prem, in the cloud or even across clouds, all as a single store. It is a simple and straightforward bridge to your future, cloud-based data architecture.
    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.
    Firebase
    Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.
    See all alternatives