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ease
features
design
support

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Description

Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale. It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation. With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently. Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL. Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes. Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management. Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.

Description

Facilitates seamless data exchange among components within microservice architectures. When utilized as a communication method for microservices, it not only streamlines integration but also enhances reliability and scalability. The system allows for reading and writing data in nearly real-time, while providing the flexibility to set data throughput and storage durations according to specific requirements. Users can finely configure resources for processing data streams, accommodating anything from small streams of 100 KB/s to more substantial ones at 100 MB/s. Additionally, Yandex Data Transfer enables the delivery of a single stream to various targets with distinct retention policies. Data is automatically replicated across multiple availability zones that are geographically distributed, ensuring redundancy and accessibility. After the initial setup, managing data streams can be done centrally through either the management console or the API, offering convenient oversight. It also supports continuous data collection from diverse sources, including website browsing histories and application logs, making it a versatile tool for real-time analytics. Overall, Yandex Data Streams stands out for its robust capabilities in handling various data ingestion needs across different platforms.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Kinesis
Amazon S3
Apache Flink
Apache Hive
Apache Hudi
Apache Kafka
Apache Spark
Baidu Palo
ClickHouse
MySQL
OpenMetadata
PostgreSQL
SelectDB
TapData
VeloDB
Yandex Cloud
Yandex Data Transfer

Integrations

Amazon Kinesis
Amazon S3
Apache Flink
Apache Hive
Apache Hudi
Apache Kafka
Apache Spark
Baidu Palo
ClickHouse
MySQL
OpenMetadata
PostgreSQL
SelectDB
TapData
VeloDB
Yandex Cloud
Yandex Data Transfer

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$0.086400 per GB
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

doris.apache.org

Vendor Details

Company Name

Yandex

Founded

1997

Country

Russia

Website

cloud.yandex.com/en/services/data-streams

Product Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Alternatives

Alternatives