What is BDS?
It is a realtime data aggregating, analyzing and visualization service for chain-like unstructured data from all kinds of 3rd party Blockchains.
BDS is a tool in the Blockchain category of a tech stack.
BDS is an open source tool with 487 GitHub stars and 43 GitHub forks. Here’s a link to BDS's open source repository on GitHub
PostgreSQL, Kafka, Microsoft SQL Server, Grafana, and Confluent are some of the popular tools that integrate with BDS. Here's a list of all 5 tools that integrate with BDS.
Why developers like BDS?
Here’s a list of reasons why companies and developers use BDS
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- Cover dozens of well-known Blockchain projects, including BTC, ETH, LTC, XRP, BCH, etc
- Provide an interactive data visualization BI tool
- Support standard SQL Query statements so that complex query logics can be implemented easily
- Provide products that query data on the Blockchain in China and it also provides data visualization BI tools
BDS Alternatives & Comparisons
What are some alternatives to BDS?
See all alternatives
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 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 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.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes.
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.