Amazon Timestream vs BTrDB

Amazon Timestream is a managed cloud service offering time-series database engines for low-latency queries and large-scale ingestion. Timestream for LiveAnalytics scales ingestion, storage and query capacity independently and can process millions of queries. Memory and magnetic tiers support retention rules that move data and delete older records. Timestream for InfluxDB 3 Enterprise supports clusters of up to 15 nodes assigned to ingestion, query or compaction work. Backups can run hourly, daily, weekly, monthly or on a custom cron schedule, with retention from one to 365 days; on-demand backups can remain for up to 3,650 days. AWS states that data is encrypted by default and documents IAM, KMS and AWS Backup integrations. Ingestion options include SDKs, CLI, WriteRecords API, Lambda, IoT Core, Kinesis, MSK, Managed Service for Apache Flink and Telegraf. SQL, Flux and InfluxQL are supported query languages.

BTrDB is a free, MIT-licensed, self-hosted time-series database for dense, high-precision univariate data. It partitions data by time, supports clustered deployments, and records stream changes as new versions that queries can target. Streams have unique UUIDs and can be grouped into collections with tags and annotations. The Python btrdb package supports nanosecond-timestamp queries and insertion through Stream.insert, PyArrow tables, or pandas DataFrames. Statistical queries can return minimum, maximum, mean, count, and standard deviation without reading every underlying point. StreamSets can be filtered and converted to pandas DataFrames or CSV files. Documentation shows Dash and Plotly visualization, Ray-worker serialization, TLS on port 4411, and API-key authentication requiring that TLS port. Arrow-based tabular methods are documented for commercial customers with Arrow-enabled servers. BTrDB reports measured cluster throughput and compression figures, and describes smart-grid aggregation at city or country scale as one target use case.