TimescaleDB vs LeanXcale

Overview

TimescaleDB

Stacks226

Followers374

Votes44

GitHub Stars20.6K

Forks988

LeanXcale

Stacks1

Followers4

Votes0

TimescaleDB vs LeanXcale: What are the differences?

TimescaleDB: Scalable and reliable time-series SQL database optimized for fast ingest and complex queries. Built on PostgreSQL. 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; LeanXcale: A scalable SQL database with fast NoSQL data ingestion and GIS capabilities. It is a scalable SQL database with fast NoSQL data ingestion and GIS capabilities. It simplifies your architecture thanks to its combination of SQL and NoSQL capabilities. Move faster from customer needs detection to production avoiding complex architectures such as lambda. Development is made easy using the SQL API.

TimescaleDB can be classified as a tool in the "Databases" category, while LeanXcale is grouped under "SQL Database as a Service".

Some of the features offered by TimescaleDB are:

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

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

Rapid data ingestion
Powerful SQL & GIS
Linear scalability

TimescaleDB is an open source tool with 8.82K GitHub stars and 485 GitHub forks. Here's a link to TimescaleDB's open source repository on GitHub.

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Advice on TimescaleDB, LeanXcale

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

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

TimescaleDB	LeanXcale
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.	It is a scalable SQL database with fast NoSQL data ingestion and GIS capabilities. It simplifies your architecture thanks to its combination of SQL and NoSQL capabilities. Move faster from customer needs detection to production avoiding complex architectures such as lambda. Development is made easy using the SQL API.
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;	Rapid data ingestion; Powerful SQL & GIS ; Linear scalability
Statistics
GitHub Stars 20.6K	GitHub Stars -
GitHub Forks 988	GitHub Forks -
Stacks 226	Stacks 1
Followers 374	Followers 4
Votes 44	Votes 0
Pros & Cons
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	No community feedback yet
Integrations
Prometheus Equinix Metal Ruby PostgreSQL Django Kubernetes pgAdmin Python Kafka Datadog	.NET Apache Spark Python Kafka Java Linux Windows

What are some alternatives to TimescaleDB, LeanXcale?

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.

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 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.

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.