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InfluxDB vs OpenTSDB: What are the differences?
Introduction
InfluxDB and OpenTSDB are both time series databases used for storing and analyzing time series data. While they serve the same purpose, there are several key differences between the two.
Data Model: InfluxDB uses a key-value store with a flexible schema, allowing for the storage of different types of data within the same measurement or series. OpenTSDB, on the other hand, follows a strict schema with fixed tags and metrics, which can limit the flexibility in data storage and retrieval.
Query Language: InfluxDB uses a SQL-like query language called InfluxQL, which offers a wide range of query capabilities including aggregations, joins, and functions. OpenTSDB uses a simplified query language that requires specifying the metric, tags, and time range explicitly, making it less versatile compared to InfluxDB.
Scalability: InfluxDB is designed to be highly scalable and can handle large volumes of data with ease. It provides built-in clustering and sharding capabilities, allowing for horizontal scaling across multiple nodes. OpenTSDB, on the other hand, relies on HBase for storage and scalability, which may require additional configuration and setup.
Data Storage: InfluxDB stores data in its own custom time series file format, which is optimized for efficient data compression and retrieval. OpenTSDB, on the other hand, relies on HBase as its underlying storage system, which may introduce additional complexities and dependencies to the setup.
Ease of Setup: InfluxDB offers a single binary distribution that can be easily installed and set up on various operating systems. It also provides a web-based admin interface for configuration and management. OpenTSDB, on the other hand, requires a multi-component setup, including HBase and ZooKeeper, which may require more effort and technical expertise.
Community and Ecosystem: InfluxDB has a vibrant and active community with extensive documentation, libraries, and integrations with popular tools and frameworks. OpenTSDB, while also having a dedicated user base, may have a smaller community and a more limited ecosystem in terms of available libraries and integrations.
In summary, InfluxDB and OpenTSDB differ in their data model, query language, scalability, data storage, ease of setup, and community ecosystem. While both are capable time series databases, InfluxDB offers more flexibility and a wider range of features, making it a popular choice for many time series data applications.
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
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.
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.
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.
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
Pros of InfluxDB
- Time-series data analysis59
- Easy setup, no dependencies30
- Fast, scalable & open source24
- Open source21
- Real-time analytics20
- Continuous Query support6
- Easy Query Language5
- HTTP API4
- Out-of-the-box, automatic Retention Policy4
- Offers Enterprise version1
- Free Open Source version1
Pros of OpenTSDB
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Cons of InfluxDB
- Instability4
- Proprietary query language1
- HA or Clustering is only in paid version1