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rqlite

10
38
+ 1
1
TimescaleDB

212
368
+ 1
44
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rqlite vs TimescaleDB: What are the differences?

rqlite: The lightweight, distributed relational database built on SQLite. rqlite is a distributed relational database, which uses SQLite as its storage engine. rqlite uses Raft to achieve consensus across all the instances of the SQLite databases, ensuring that every change made to the system is made to a quorum of SQLite databases, or none at all; 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.

rqlite and TimescaleDB can be categorized as "Databases" tools.

rqlite and TimescaleDB are both open source tools. It seems that TimescaleDB with 7.28K GitHub stars and 385 forks on GitHub has more adoption than rqlite with 4.64K GitHub stars and 259 GitHub forks.

Advice on rqlite and TimescaleDB
Umair Iftikhar
Technical Architect at ERP Studio · | 3 upvotes · 431.6K views
Needs advice
on
CassandraCassandraDruidDruid
and
TimescaleDBTimescaleDB

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.

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Replies (1)
Recommends
on
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.

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Needs advice
on
InfluxDBInfluxDBMongoDBMongoDB
and
TimescaleDBTimescaleDB

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

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Replies (3)
Yaron Lavi
Recommends
on
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.

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Recommends
on
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.

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Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 318.9K views
Recommends
on
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.

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Decisions about rqlite and TimescaleDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 132.6K 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

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Pros of rqlite
Pros of TimescaleDB
  • 1
    So easy
  • 9
    Open source
  • 8
    Easy Query Language
  • 7
    Time-series data analysis
  • 5
    Established postgresql API and support
  • 4
    Reliable
  • 2
    Paid support for automatic Retention Policy
  • 2
    Chunk-based compression
  • 2
    Postgres integration
  • 2
    High-performance
  • 2
    Fast and scalable
  • 1
    Case studies

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Cons of rqlite
Cons of TimescaleDB
    Be the first to leave a con
    • 5
      Licensing issues when running on managed databases

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    What is rqlite?

    rqlite is a distributed relational database, which uses SQLite as its storage engine. rqlite uses Raft to achieve consensus across all the instances of the SQLite databases, ensuring that every change made to the system is made to a quorum of SQLite databases, or none at all.

    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.

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    What are some alternatives to rqlite and TimescaleDB?
    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.
    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.
    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.
    Microsoft SQL Server
    Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
    See all alternatives