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  1. Stackups
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  4. Databases
  5. Azure SQL Database vs TimescaleDB

Azure SQL Database vs TimescaleDB

OverviewDecisionsComparisonAlternatives

Overview

Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13
TimescaleDB
TimescaleDB
Stacks226
Followers374
Votes44
GitHub Stars20.6K
Forks988

Azure SQL Database vs TimescaleDB: What are the differences?

Azure SQL Database: Managed, intelligent SQL in the cloud. It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software; 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.

Azure SQL Database and TimescaleDB belong to "Databases" category of the tech stack.

TimescaleDB is an open source tool with 7.39K GitHub stars and 393 GitHub forks. Here's a link to TimescaleDB's open source repository on GitHub.

According to the StackShare community, Azure SQL Database has a broader approval, being mentioned in 21 company stacks & 20 developers stacks; compared to TimescaleDB, which is listed in 21 company stacks and 19 developer stacks.

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Advice on Azure SQL Database, TimescaleDB

Anonymous
Anonymous

Apr 21, 2020

Needs advice

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

381k views381k
Comments
Benoit
Benoit

Principal Engineer at Sqreen

Sep 21, 2019

Decided

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

155k views155k
Comments

Detailed Comparison

Azure SQL Database
Azure SQL Database
TimescaleDB
TimescaleDB

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

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.

-
Packaged as a PostgreSQL extension;Full ANSI SQL;JOINs (e.g., across PostgreSQL tables);Complex queries;Secondary indexes;Composite indexes;Support for very high cardinality data;Triggers;Constraints;UPSERTS;JSON/JSONB;Ability to ingest out of order data;Ability to perform accurate rollups;Data retention policies;Fast deletes;Integration with PostGIS and the rest of the PostgreSQL ecosystem;
Statistics
GitHub Stars
-
GitHub Stars
20.6K
GitHub Forks
-
GitHub Forks
988
Stacks
585
Stacks
226
Followers
502
Followers
374
Votes
13
Votes
44
Pros & Cons
Pros
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable
Pros
  • 9
    Open source
  • 8
    Easy Query Language
  • 7
    Time-series data analysis
  • 5
    Established postgresql API and support
  • 4
    Reliable
Cons
  • 5
    Licensing issues when running on managed databases
Integrations
No integrations available
Prometheus
Prometheus
Equinix Metal
Equinix Metal
Ruby
Ruby
PostgreSQL
PostgreSQL
Django
Django
Kubernetes
Kubernetes
pgAdmin
pgAdmin
Python
Python
Kafka
Kafka
Datadog
Datadog

What are some alternatives to Azure SQL Database, TimescaleDB?

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.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

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.

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