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Datastax Enterprise System Properties
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|Editorial information provided by DB-Engines|
|Description||DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.|
|Primary database model||Wide column store|
|Secondary database models||Document store|
|Current release||6.8, April 2020|
|License Commercial or Open Source||commercial|
|Cloud-based only Only available as a cloud service||no|
|DBaaS offerings (sponsored links) Database as a Service|
Providers of DBaaS offerings, please contact us to be listed.
|Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.|
|Server operating systems||Linux|
|Typing predefined data types such as float or date||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no|
|SQL Support of SQL||SQL-like DML and DDL statements (CQL); Spark SQL|
|APIs and other access methods||Proprietary protocol CQL (Cassandra Query Language)|
TinkerPop Gremlin with DSE Graph
|Supported programming languages||C|
|Server-side scripts Stored procedures||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding no "single point of failure"|
|Replication methods Methods for redundantly storing data on multiple nodes||configurable replication factor, datacenter aware, advanced replication for edge computing|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency|
Tunable Consistency consistency level can be individually decided with each write operation
|Foreign keys Referential integrity||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no Atomicity and isolation are supported for single operations|
|Concurrency Support for concurrent manipulation of data||yes|
|Durability Support for making data persistent||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes|
|User concepts Access control||Access rights for users can be defined per object|
|More information provided by the system vendor|
DataStax Enterprise is scale-out data infrastructure for enterprises that need to handle any workload in any cloud.
Supporting the following application requirements:
|Typical application scenarios|
Applications that must be massively and linearly scalable with 100% uptime and able to be deployed in a cloud-native, multi-cloud, or hybrid cloud model.
Customer 360, Personalization and Recommendations, Loyalty Programs, Consumer Fraud Protection, eCommerce, Inventory Management, Asset Monitoring, Supply Chain Management, Logistics, Security & Compliance and Identity Management.
Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and Walmart
Among the Forbes 100 Most Innovative Companies, DataStax is trusted by
|Licensing and pricing models|
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|Recent citations in the news|
DataStax taps ThirdAI to bring generative AI to its database offerings
DataStax review: Cassandra made faster and easier
DataStax Announces DataStax Enterprise 6.7
US Bank is using DataStax Enterprise to overcome legacy and become customer focused
Datastax Launches Tech Support for Open Source Cassandra
provided by Google News
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