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  5. Managed Elasticsearch vs Quickwit

Managed Elasticsearch vs Quickwit

OverviewComparisonAlternatives

Overview

Managed Elasticsearch
Managed Elasticsearch
Stacks0
Followers5
Votes0
Quickwit
Quickwit
Stacks3
Followers8
Votes10
GitHub Stars10.5K
Forks491

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Detailed Comparison

Managed Elasticsearch
Managed Elasticsearch
Quickwit
Quickwit

It is a fully managed Elasticsearch solution built on your environment, whether it is in the cloud or on-prem, providing enhanced security, reduced latency, and reduced costs compared to externally hosted Elasticsearch. We provide reliable, secure data ingestion and search, analysis, and visualization in real-time, while you retain full authority over your data.

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.

Routine Backups; Support for ALL versions of Elasticsearch, including both Elasticsearch from Elastic and Open Distro for Elasticsearch from AWS; High Availability and High Throughput; Comprehensive Elasticsearch Service; Enhanced Security
Highly scalable distributed search; Sub-second full-text search on cloud / distributed storage; Stream indexing: Kafka and Kinesis native; Exactly-once semantics at indexing: no data loss; Time-based sharding
Statistics
GitHub Stars
-
GitHub Stars
10.5K
GitHub Forks
-
GitHub Forks
491
Stacks
0
Stacks
3
Followers
5
Followers
8
Votes
0
Votes
10
Pros & Cons
No community feedback yet
Pros
  • 2
    Open-source
  • 2
    Written in Rust
  • 2
    Scalable
  • 2
    Fast search
  • 2
    Great Search Engine
Integrations
Elasticsearch
Elasticsearch
PostgreSQL
PostgreSQL
Kafka
Kafka
Kubernetes
Kubernetes
Minio
Minio
ceph
ceph
Amazon Kinesis
Amazon Kinesis

What are some alternatives to Managed Elasticsearch, Quickwit?

Elasticsearch

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

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