Google Cloud Datastore vs Xplenty
Overview
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Detailed Comparison
Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage. Once done processing, Xplenty allows you to connect with Amazon Redshift, SAP HANA and Google BigQuery. You can also store processed data back in your favorite relational database, cloud storage or key-value store. | Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries. |
Xplenty provides you with an visual, intuitive interface to design your ETL data flows; Xplenty lets you integrate data from a variety of data stores, such as Amazon RDS, MySQL, PostgreSQL, Microsoft SQL Server and MongoDB.; Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage; Once done processing, Xplenty allows you to connect with Amazon Redshift, SAP HANA and Google BigQuery. You can also store processed data back in your favorite relational database, cloud storage or key-value store;Integrate semi-structured data with structured data. Our package designer makes it a snap for every data and BI user to write complex data flows for your flat files and JSON files on top of Hadoop without writing a single line of code. | Schemaless access, with SQL-like querying;Managed database;Autoscale with your users;ACID transactions;Built-in redundancy;Local development tools |
Statistics | |
Stacks 12 | Stacks 290 |
Followers 26 | Followers 357 |
Votes 2 | Votes 12 |
Pros & Cons | |
Pros
| Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Xplenty, Google Cloud Datastore?
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
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.
Azure Cosmos DB
Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
Cloud Firestore
Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.
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.
Amazon EMR
It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.
Cloudant
Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.
Altiscale
we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.
Snowflake
Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
