Dremio vs Monosi
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts. | It is a stand-alone platform for data observability and monitoring. It ensures data quality by automatically monitoring your data stack for anomalies, alerting you of issues, and analyzing the root cause. |
Democratize all your data;
Make your data engineers more productive;
Accelerate your favorite tools;
Self service, for everybody
| Profile & setup basic data quality monitors in minutes;
No-code, stand-alone full web application;
Automated, built-in scheduler & jobs;
Integrate & monitor your entire data stack |
Statistics | |
GitHub Stars - | GitHub Stars 326 |
GitHub Forks - | GitHub Forks 34 |
Stacks 116 | Stacks 1 |
Followers 348 | Followers 6 |
Votes 8 | Votes 0 |
Pros & Cons | |
Pros
Cons
| No community feedback yet |
Integrations | |
What are some alternatives to Dremio, Monosi?
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
Kibana
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Google BigQuery
Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Amazon Redshift
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Nagios
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
Netdata
Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps
Qubole
Qubole is a cloud based service that makes big data easy for analysts and data engineers.
Zabbix
Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.
