LeanXcale vs QuestDB

Overview

LeanXcale

Stacks1

Followers4

Votes0

QuestDB

Stacks19

Followers50

Votes17

GitHub Stars16.3K

Forks1.5K

LeanXcale vs QuestDB: What are the differences?

Developers describe LeanXcale as "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. On the other hand, QuestDB is detailed as "Open source database for time series, events, and analytical workloads". It is an open source database for time series, events, and analytical workloads with a primary focus on performance. It enhances ANSI SQL with time series extensions to manipulate time stamped data.

LeanXcale and QuestDB are primarily classified as "SQL Database as a Service" and "Databases" tools respectively.

Some of the features offered by LeanXcale are:

Rapid data ingestion
Powerful SQL & GIS
Linear scalability

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

SIMD optimised analytics
Rows and columns based access
Vectorized queries execution

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Detailed Comparison

LeanXcale	QuestDB
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.	QuestDB is an open source database for time series, events, and analytical workloads with a primary focus on performance. It enhances ANSI SQL with time series extensions.
Rapid data ingestion; Powerful SQL & GIS ; Linear scalability	Relational model for time series; SIMD accelerated queries; Time partitioned; Heavy parallelization; Scalable ingestion; Immediate consistency; Time series and relational joins; Native InfluxDB line protocol; Grafana through Postgres wire support; Schema or schema-free; Aggregations and down sampling
Statistics
GitHub Stars -	GitHub Stars 16.3K
GitHub Forks -	GitHub Forks 1.5K
Stacks 1	Stacks 19
Followers 4	Followers 50
Votes 0	Votes 17
Pros & Cons
No community feedback yet	Pros 2 Real-time analytics 2 Time-series data analysis 2 Open source 2 SQL 2 Postgres wire protocol
Integrations
.NET Apache Spark Python Kafka Java Linux Windows	InfluxDB Java PostgreSQL

What are some alternatives to LeanXcale, QuestDB?

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.