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InfluxDB vs ObjectBox: What are the differences?
InfluxDB and ObjectBox are two popular database management systems with distinct features and use cases. InfluxDB is a time-series database designed for handling high volumes of timestamped data efficiently, commonly used in monitoring and IoT applications. On the other hand, ObjectBox is a mobile database that offers fast and efficient storage and retrieval of data on mobile devices without relying on a server.
Data Structure: InfluxDB stores data in a highly optimized time-series data structure, making it suitable for time-sensitive queries and analysis. ObjectBox, on the other hand, uses an object-oriented approach to store data in a schema-less format, providing flexibility in data modeling and retrieval.
Query Language: InfluxDB uses InfluxQL, a SQL-like query language optimized for time-series data operations, allowing for complex analytical queries and aggregations. ObjectBox utilizes an intuitive API and query language that simplifies data manipulation for mobile applications and reduces the overhead of managing complex queries.
Storage Efficiency: InfluxDB optimizes data storage through efficient compression algorithms and indexing strategies, reducing the disk space required for storing large volumes of time-series data. ObjectBox offers a compact storage format that minimizes the storage footprint on mobile devices, ensuring optimal performance and data access.
Scalability: InfluxDB is designed for horizontal scalability, allowing users to expand their database clusters to accommodate growing data volumes and query loads. ObjectBox focuses on providing efficient local storage and retrieval capabilities for individual devices, offering scalability through data synchronization mechanisms.
Integration: InfluxDB offers robust integration capabilities with various data sources and visualization tools, facilitating seamless data ingestion and analysis workflows in diverse environments. ObjectBox prioritizes local data management on mobile devices, supporting integration with backend services for data synchronization and remote access.
Community and Support: InfluxDB has a strong open-source community and active development, providing users with comprehensive documentation, tutorials, and forums for support and collaboration. ObjectBox offers dedicated support and resources for mobile developers, including sample code, integration guides, and personalized assistance for optimizing database performance on mobile platforms.
In Summary, InfluxDB and ObjectBox differ in their data structures, query languages, storage efficiency, scalability, integration options, and support ecosystems, catering to distinct use cases in time-series data analysis and mobile data management.
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 analysis58
- 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 ObjectBox
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Cons of InfluxDB
- Instability4
- Proprietary query language1
- HA or Clustering is only in paid version1
Cons of ObjectBox
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