>>> Злобность (Malevolent) <<<
Джексон и Энджела зарабатывают на жизнь тем, что притворяются экстрасенсами и делают вид, что избавляют людей от привидений, в которых они сами не верят. Но однажды всё идёт не по плану.
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Сериал datastax cassandra jdbc driver посмотреть
SQL up-leveling provides the capability to write a SQL statement that can be executed across multiple databases, regardless of the databases’ SQL implementation. For example, a SQL statement written against Oracle will also be interoperable with DB2.
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Progress DataDirect management of packet-based network communication provides unsurpassed packet transport, network round trips and data buffering optimization. (socket management). Includes performance methodology for throughput and resource utillization (CPU/memory)
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Day One Support for disruptive technologies with frequent release cycles. With this strategy - the first of its kind for any data connectivity provider - Progress DataDirect on-premises ODBC and JDBC drivers will support any new versions of supported data sources.
Type 5 JDBC drivers offer the same client-side, single-tier, 100% Java architecture of Type 4 JDBC drivers, but address the limitations of many of the Type 4 JDBC drivers. Unlike a type 4 JDBC driver, our type 5 JDBC driver maximizes data throughput while using minimal amount of CPU and memory resources. You can learn more over
Data Connectivity is a critical, but often overlooked component of the IT infrastructure. These components have dramatic effects on application performance, reliability and portability. Learn about the top 10 reasons high-performance data connectivity is critical for your business.
Apache Spark provides a uniform API for workflows over diverse systems and runtimes. The biggest advantage of Spark is its speed—up to 100 times faster than Hadoop Map Reduce in memory and 10 times faster on disk. Spark SQL allows users to use JDBC driver to run SQL queries and unlock real-time analytics on Big Data systems through spark. Try our Spark SQL JDBC driver now.
The growing popularity of NoSQL is wreaking havoc on core business system integrations in organizations of all sizes. NoSQL databases have query languages and frameworks to better support SQL-like operations, but they are still incompatible with existing SQL-based infrastructures. Join Progress and Software AG to learn more about the industry's leading suite of production-ready ODBC connectors for SQL on NoSQL databases.
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Cassandra has always benefited from a great architecture, thought from the very beginning for scalability, performance and availability. This is surely what has driven its tremendous success so far. Unfortunately, early versions of Cassandra also came with a rather complex interface and data model that were negatively impacting the learning curve for developers. To solve this issue the Apache Cassandra team came up with a great new language and abstraction: . This clearly renewed the face of Cassandra, bringing a consistent interface across all languages and tools.
Thrift, the transport layer that Cassandra traditionally used for client-server communication, has been a great opportunity for the database in its early days since Thrift clients were readily available for most programming languages. This allowed the Apache Cassandra project to focus on the server side without spreading their resources on the client side. Nevertheless, as Cassandra became mature, Thrift turned out to be a limitation: communication limited to the request-response paradigm, no notifications, no streaming, client side interface made of generated code, etc. In Cassandra 1.2, a solution to this second problem was introduced with the , a protocol designed exclusively for CQL3 and with enough flexibility to enable new features in Cassandra for the years to come.
With these two majors changes, an update was obviously necessary on the client side. The fact that we had a renewed interface and transport layer, together with the need for an environment free of any Thrift concepts, strongly advocated for a brand new line of drivers, which was aligned with the long-term strategy of CQL.
Today, DataStax announces version 1.0.0 of a new , designed for CQL and based on years of experience within the Cassandra community. This Java driver is a first step; an object mapping and a JDBC extension will be available soon, drivers for C# and other major languages are on their way. Besides this new interface and API, this new driver comes with.
In the weeks to come, several articles on this blog will cover some particular features of this Java Driver. Meanwhile, its is readily available and you can start to use it right away using the following Maven dependency.
DataStax is pleased to make available an ODBC driver for that can be used free of charge with both open source Cassandra and . Using the DataStax ODBC driver for Cassandra, you can connect to a database cluster with your favorite BI tools (e.g. Tableau, Microsoft Excel, etc.) or other development software and access data stored on Cassandra nodes.
The DataStax ODBC driver for Cassandra was developed by ODBC software leader Simba Corporation and is compliant with the latest ODBC 3.52 specification and runs on both 32 and 64-bit platforms.
Installing the DataStax ODBC driver for Cassandra is simple. The only prerequisite needed for Windows is to have the Microsoft Visual C++ 2010 runtime installed for the appropriate platform (either 32 or 64-bit).
Then, you create either a User or System DSN (data source name) that will be used by front end business intelligence tools. You’ll need to enter a name for the datasource as well as the IP or host name of the Cassandra node you want to connect to, along with a keyspace that will be referenced by the driver. Once the information is entered, you can test your connection to ensure it connect to your cluster.
Note that the current driver does not currently support version 3.0 of the Cassandra Query Language (CQL3), which is the default for Cassandra 1.2 and higher (an upcoming version of the driver will support CQL3). However, CQL2 is supported, so you will want to make sure that any objects you want to reference with the driver are created with CQL2.
The Windows installer for Cassandra 1.2 and higher uses CQL3 by default and creates a shortcut for the CQL utility that can be easily clicked on and run. To create a CQL utility shortcut that uses CQL2, just create a new shortcut with the following target executable (substituting your install location if you changed it from the default location).
Once you’ve successfully configured your ODBC datasource, you can use it in your preferred BI tools to connect to and pull data back from Cassandra. For example, to use the DataStax ODBC driver for Cassandra with Microsoft Excel, you can use the data connection wizard to select your new ODBC datasource.
DataStax Enterprise 6.8 accelerates cloud-native and bare-metal performance, supports moreworkload types from graph to search and analytics, and improves user productivity withKubernetes and APIs.
With the Early Adopter Program release of DSE, you’ll get a chance to work with the latest version of DSE before it becomes GA. Take advantage of 4 times faster scaling. Be a more productive Cassandra developer with cross-partition Graph queries on Cassandra. Plus so much more.
Preview version of an open source tool that enables developers to run their AWS DynamoDB™ workloads on Apache Cassandra™. With the proxy, developers can run DynamoDB workloads outside of AWS (including on premises, other clouds, and in hybrid configurations).
DataStax CDC for Apache Kafka extends are existing Sink Connector with Source functionality. Now changes may be pushed from a source DataStax Enterprise cluster to Kafka topics. Change Data Capture events include inserts, updates, and deletes.
DataStax Enterprise (DSE) is a distributed multi-model database built on Apache Cassandra. The DSE Operator for Kubernetes simplifies the process of deploying and managing DSE in a Kubernetes cluster.
DSBench is a performance testing tool that makes workload simulation for DataStax Enterprise and Apache Cassandra a breeze. You can use it anywhere you need to put a realistic load on a target cluster to characterize performance.
Apache Cassandra™ is a distributed database that delivers the high availability, performance, and linear scalability today’s most demanding applications require. It offers operational simplicity and effortless replication across cloud service providers, data centers, and geographies, and it can handle petabytes of information and thousands of concurrent operations per second across hybrid cloud environments.
From its inception, Cassandra has been the premier distributed database on the market, and here at DataStax, we remain committed to continuing that legacy. DataStax offers production-certified Cassandra distributions plus 24x7x365 expert support to ensure all Cassandra users can make the most of this powerful database.
DataStax Luna provides subscription-based support for open source Cassandra to help ensure you meet required service levels while providing your team with the confidence they need to deploy and run their applications.
The data management needs of the average large organization have changed dramatically over the last ten years, requiring data architects, operators, designers, and developers to rethink the databases they use as their foundation. The proliferation of large-scale, globally distributed data led to the birth of Apache Cassandra™, one of the world’s most powerful and now most popular NoSQL databases. Read this white paper to learn how Cassandra was born, how it’s evolved, how it operates, and what DataStax Distribution of Apache Cassandra™ adds to the equation.
DSE includes twice the horsepower of Apache Cassandra, delivering twice the throughput to handle twice the workloads with the same hardware. Plus DataStax Bulk Loader makes loading and unloading data a snap.
A major challenge of Apache Cassandra is operational management. Repairing nodes for synchronization is an intensely manual process that requires the right expertise. DSE NodeSync removes that pain, eliminating 90% of such manual operations. So even novice DBAs and DevOps professionals can run DSE like seasoned professionals.
Apache Cassandra includes only basic security such as login and password. DSE adds comprehensive, enterprise-grade s
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