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Back to transceptor-technology/siridb-server

Open-source alternatives to Siridb Server

15 open-source projects similar to transceptor-technology/siridb-server, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Siridb Server alternative.

  • akumuli/akumuliakumuli avatar

    akumuli/Akumuli

    840View on GitHub↗

    Time-series database

    C++
    View on GitHub↗840
  • dalmatinerdb/dalmatinerdbdalmatinerdb avatar

    dalmatinerdb/dalmatinerdb

    692View on GitHub↗

    See gitlab: https://gitlab.com/Project-FiFo/DalmatinerDB/dalmatinerdb

    Erlang
    View on GitHub↗692
  • druid-io/druiddruid-io avatar

    druid-io/druid

    14,020View on GitHub↗

    Druid is a distributed columnar store and online analytical processing database designed for real-time analytics. It functions as a SQL analytics platform and a streaming data ingestion engine, allowing for the analysis of large datasets with low latency to support interactive dashboards and high-concurrency operational workloads. The system integrates a streaming data ingestion engine that loads information via batch or streaming processes to enable immediate analysis of arriving data. It provides high-performance analytical processing to execute slice-and-dice queries on massive data volume

    Java
    View on GitHub↗14,020
  • facebookincubator/beringeifacebookincubator avatar

    facebookincubator/beringei

    3,154View on GitHub↗

    Beringei is a high performance, in-memory storage engine for time series data.

    C++
    View on GitHub↗3,154
  • improbable-eng/thanosimprobable-eng avatar

    improbable-eng/thanos

    14,105View on GitHub↗

    Thanos is a CNCF cloud native monitoring tool that provides a highly available and scalable extension to the Prometheus ecosystem. It functions as a global query engine, a long-term storage system, and a metric downsampler. The project enables a unified interface to aggregate and query metrics across multiple distributed clusters from a single view. It maintains historical data beyond local retention limits by persisting time-series metrics in object storage and eliminates data gaps by merging metrics from redundant server pairs. The system includes capabilities for reducing the resolution o

    Go
    View on GitHub↗14,105

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  • kairosdb/kairosdbkairosdb avatar

    kairosdb/kairosdb

    1,759View on GitHub↗

    Fast scalable time series database

    Java
    View on GitHub↗1,759
  • manahl/arcticmanahl avatar

    manahl/arctic

    3,090View on GitHub↗

    High performance datastore for time series and tick data

    Python
    View on GitHub↗3,090
  • nationalsecurityagency/timelyNationalSecurityAgency avatar

    NationalSecurityAgency/timely

    392View on GitHub↗

    Accumulo backed time series database

    Java
    View on GitHub↗392
  • opentsdb/opentsdbOpenTSDB avatar

    OpenTSDB/opentsdb

    5,068View on GitHub↗

    OpenTSDB is a distributed time series database and metrics engine designed for storing and managing massive volumes of high-cardinality system metrics. It functions as a data store and analytics platform that enables large-scale metric ingestion and infrastructure performance monitoring across a distributed cluster. The system distinguishes itself through a distributed storage abstraction that supports multiple backends such as HBase, Cassandra, and Google Bigtable. It utilizes a hierarchical metric tree to organize time series and employs numeric identifier indexing to reduce storage footpri

    Java
    View on GitHub↗5,068
  • pardot/rhombusP

    Pardot/Rhombus

    0View on GitHub↗
    View on GitHub↗0
  • questdb/questdbquestdb avatar

    questdb/questdb

    17,062View on GitHub↗

    QuestDB is a high-performance, distributed time-series database designed for the ingestion, storage, and analysis of massive datasets. It functions as a real-time analytics platform that utilizes a columnar storage engine to optimize disk input and output, enabling efficient analytical scans and complex windowing operations on streaming data. The platform distinguishes itself through specialized capabilities for handling asynchronous time-series streams, including advanced join algorithms that align disparate data sets based on precise timestamp lookups. It supports high-volume ingestion thro

    Javacapital-marketscppdatabase
    View on GitHub↗17,062
  • rackerlabs/bluefloodrackerlabs avatar

    rackerlabs/blueflood

    598View on GitHub↗

    A distributed system designed to ingest and process time series data

    Java
    View on GitHub↗598
  • taosdata/tdenginetaosdata avatar

    taosdata/TDengine

    24,734View on GitHub↗

    TDengine is a distributed time-series database designed for the high-speed ingestion, compression, and retrieval of timestamped metrics and sensor data. It functions as a SQL-compatible analytics engine, allowing users to perform complex operations on massive volumes of time-ordered information using standard relational syntax. The platform is built to serve as a backend foundation for industrial IoT environments, managing real-time data streams and device metadata through a cluster-based architecture. The system distinguishes itself through a distributed sharding architecture that uses consi

    Cbigdatacloud-nativecluster
    View on GitHub↗24,734
  • timescale/timescaledbtimescale avatar

    timescale/timescaledb

    21,876View on GitHub↗

    TimescaleDB is an open-source PostgreSQL extension that adds native time-series capabilities to the database. At its core, it transforms standard PostgreSQL tables into hypertables—automatically partitioned by time intervals—so data is stored in fixed-size chunks without manual sharding. The extension includes a library of over 200 built-in SQL functions purpose-built for time-series workloads, such as time bucketing, gap filling, percentile estimation, and time-weighted averages. What distinguishes TimescaleDB from generic PostgreSQL is its set of integrated time-series features that work th

    Canalyticsdatabasefinancial-analysis
    View on GitHub↗21,876
  • victoriametrics/victoriametricsVictoriaMetrics avatar

    VictoriaMetrics/VictoriaMetrics

    16,343View on GitHub↗

    VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct

    Godatabasegrafanagraphite
    View on GitHub↗16,343