AWS SimSpace Weaver vs Dremio
Overview
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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 new compute service to run real-time spatial simulations in the cloud and at scale. With SimSpace Weaver, simulation developers are no longer limited by the compute and memory of their hardware. |
Democratize all your data;
Make your data engineers more productive;
Accelerate your favorite tools;
Self service, for everybody
| Understand possible real-world outcomes and visualize immersive environments with massive, city-scale 3D simulations;
Increase the size, complexity, and number of objects in your simulations, distributed across instances fully managed by SimSpace Weaver;
Avoid time-consuming challenges surrounding data management, replication, and time synchronization across servers;
Integrate seamlessly with popular development toolkits and simulation engines, such as Unreal Engine and Unity |
Statistics | |
Stacks 116 | Stacks 0 |
Followers 348 | Followers 1 |
Votes 8 | Votes 0 |
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What are some alternatives to Dremio, AWS SimSpace Weaver?
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.
Qubole
Qubole is a cloud based service that makes big data easy for analysts and data engineers.
Presto
Distributed SQL Query Engine for Big Data
Amazon EMR
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
lakeFS
It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
