Overview

InfluxDB

Stacks1.1K

Followers1.2K

Votes175

Amazon QLDB

Stacks5

Followers17

Votes0

Amazon QLDB vs InfluxDB: What are the differences?

Introduction

Amazon QLDB and InfluxDB are both database solutions, but they have key differences that differentiate them in terms of functionality and use cases.

1. Data Model: Amazon QLDB uses an immutable journal design, storing every data change as a revision and making it ideal for maintaining a complete and verifiable history of changes. In contrast, InfluxDB is a time-series database optimized for handling time-stamped data, making it efficient for data that changes frequently over time.

2. Query Language: Amazon QLDB uses PartiQL, a SQL-compatible query language that allows for flexible and powerful querying capabilities. On the other hand, InfluxDB uses InfluxQL, a query language specifically designed for time-series data with functions and features tailored for analyzing time-stamped data efficiently.

3. Consistency Model: Amazon QLDB offers strong consistency guarantees, ensuring that data is always accurate and up-to-date across all reads. InfluxDB, on the other hand, offers eventual consistency by default but allows users to configure different consistency levels based on their requirements.

4. Scalability: Amazon QLDB is a fully managed service provided by AWS, offering automatic scaling capabilities that handle growing workloads seamlessly. InfluxDB, although it can be self-hosted or managed in the cloud, requires manual configuration for scaling, making it more suitable for users who prefer more control over their database infrastructure.

5. Use Cases: Amazon QLDB is commonly used for applications that require an immutable and auditable transaction log, such as financial systems or legal applications. In contrast, InfluxDB is ideal for time-series data use cases, including monitoring, IoT, and real-time analytics, where fast data ingestion and querying of time-stamped data are key requirements.

6. Ecosystem Integration: Amazon QLDB is closely integrated with other AWS services, allowing seamless interaction with storage, analytics, and application services within the AWS ecosystem. InfluxDB has its own ecosystem and integrations, with a focus on time-series data processing and visualization tools for specific use cases.

In Summary, Amazon QLDB and InfluxDB differ in their data model, query language, consistency model, scalability, use cases, and ecosystem integration, catering to distinct requirements for data storage and analysis.

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Advice on InfluxDB, Amazon QLDB

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

InfluxDB	Amazon QLDB
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.	It is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log ‎owned by a central trusted authority. It can be used to track each and every application data change and maintains a complete and verifiable history of changes over time.
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer	Immutable and Transparent; Cryptographically Verifiable; Serverless; Easy to Use; Streaming Capability
Statistics
Stacks 1.1K	Stacks 5
Followers 1.2K	Followers 17
Votes 175	Votes 0
Pros & Cons
Pros 59 Time-series data analysis 30 Easy setup, no dependencies 24 Fast, scalable & open source 21 Open source 20 Real-time analytics Cons 4 Instability 1 Proprietary query language 1 HA or Clustering is only in paid version	No community feedback yet
Integrations
No integrations available	AWS Lambda Amazon Redshift Amazon Kinesis Amazon Elasticsearch Service

What are some alternatives to InfluxDB, Amazon QLDB?

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.

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.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.