Spring announced Dijkstra’s , a Spring Data release train, General Availability release in May 20, 2014 in a blog written by Oliver Gierke, Spring Data’s Project Lead.

Dijkstra is named after Edsger Wybe Dijkstra, a Dutch computer scientist, who is known for his contributions to computer science: shortest path algorithm also known as Dijkstra’s algorithm, the Shunting Yard algorithm, the MultiProgramming System, Banker’s algorithm, and the Semaphore.

He said that the release train includes the following five new modules:

Spring Data Elasticsearch – it is led by Mohsin Husen. With Elasticsearch it is now easy to build applications that use new data access technologies and also offer improved support for relational database technologies. Spring Data Cassandra – led by David and Matthew Adams. The Apache Cassandra NoSQL Database provides new capabilities and has a similar interface to previous Spring Data modules. Both of these modules also held their first GA recently.

Spring Data Gemfire – Pivotal Gemfire is a distributed data management platform used to easily create highly scalable Spring-powered applications.

Couch base – aims to offer Spring-based programming model for new datastores while keeping store-specific features and capabilities.

Redis – offers easy configuration and access to Redis from Spring applications. It provides low-level abstraction across multiple drivers/connectors and and high-level abstractions for performing various Redis operations, exception translation and serialization support.

Listed also are other participating modules which complete the list:

Spring Data Commons 1.8 GA

Spring Data JPA 1.6 GA

Spring Data MongoDB 1.5 GA

Spring Data Neo4j 3.1 GA

Spring Data Solr 1.2 GA

Spring Data REST 2.1 GA

He mentioned that 55 tickets have been fixed prior the GA with a total of 379 tickets fixed and implemented for Dijkstra. “We’re going to drop one or two more services releases for the previous train named Codd and then concentrate on the first milestone of the next train iteration which will be named Evans.” Oliver added.

Amazon Redshift is described as a “fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools” which was initially released last February 2014. Launching data warehouse is now easier using Redshift, since it takes charge of the infrastructure which allows you to pay more attention to data and analytics.

In May 8, 2014, Amazon released a blog about the additional support for the twelve new features of Redshift which are as follows:

• JSON Support

Data in JSON format can now be loaded directly to Redshift without preprocessing. You can now specify the mapping of JSON elements to Redshift column names in a jsonpaths file using this new option.

• Copy from Elastic MapReduce

Copying of data from Elastic MapReduce cluster to a Redshift cluster is now possible using the COPY command. You can copy the following formats: fixed-width files, character-delimited files, CSV files, or JSON-formatted files.

• Unload to a Single File

Use UNLOAD command to upload the result of a query to one or more Amazon S3 files.

• Increased Concurrency

Maximum of 50 queries can now be configured simultaneously across all of your queues. The increase in the level of concurrency will let you increase your query performance on some workloads.

• Max Result Set Size

Cursor counts and result set sizes can now be configured, however, you should note that memory consumption will also increased if you use larger values.

• Regular Expression Extraction

As specified by a regular expression, substring from a string can now be taken out using the new REGEX_SUBSTR function.

• FedRAMP Approval

In April 1, 2014, Amazon announced the completion of Amazon Redshift’s FedRAMP assessment and authorization process. This has been added to their list of services covered under US East/West FedRAMP Agency Authority to Operate which is approved by the U.S. Department of Health and Human Services (HHS).

• Support for ECDHE-RSA and ECDHE-ESDCSA Cipher Suites

A pair of ECDHE key exchange protocols and the associated cipher suites are now available as choices in SSL connections to Redshift. Through this, SSL clients who chose these cipher suites can now offer perfect forward secrecy.

• Resize Progress Indicator

Monitoring the progress of cluster resize operations can now be made. You can see the information on the Redshift console and through the Redshift API.

More than a month ago, Java 8 has announced its General Availability, where other products such as Java Platform, Standard Edition (SE 8), Java Platform, Micro Edition 8 (ME 8) were included in its webcast. In April 30, Oracle has officially publicized Java ME Embedded 8 release, it’s a week after its specifications has been approved.

Java Micro Edition Embedded 8 is a Java Micro Edition (ME) 8 runtime whose specifications are aimed to have more functionalities, portability, flexibility, and security.

This release is based on Java ME Connected Limited Device Configuration (CLDC) 8 or JSR 360 and Java ME Embedded Profile (MEEP) 8 or JSR 361; it also offers the following:

• Alignment with Java SE 8 language features and API
• Updated “services-enabled” application platform
• Support to customize and “right-size” the platform
• Access from Java to a range of devices via GPIO, I2C, SPI, UART and more
• Application development is supported through the Oracle Java ME SDK 8

Oracle also listed the following key features of Java ME Embedded 8:

• Implementation of the Java ME 8 specification
• Versatile and flexible networking and connectivity, including wireless support (3GPP, CDMA, WiFi)
• Improved access to peripheral devices through Device I/O API
• Improved tooling support (Developer Agent, On-device Debugging, Memory Monitor, Network Monitor, CPU Profiler, Logging)
• New APIs for RESTful programming
• JSON API
• Async HTTP API
• OAuth 2.0 API
• Implementation of the following JSRs:
  • JSR 75 (File Connection API)
  • JSR 120 (Wireless Messaging API)
  • JSR 172 (Web Services API)
  • JSR 177 (Security and Trust Services API)
  • JSR 179 (Location API)
  • JSR 280 (XML API)
• Usability, performance, and footprint improvements over previous versions of Oracle Java ME Embedded 3.3 and 3.4

Java ME Embedded 8 is supported by wide selection of developer tools such as Oracle Java ME SDK 8 and Netbeans IDE. And supports the following platforms:

• Raspberry Pi Model B on Debian Linux
• Qualcomm IoE 6270T on Brew MP
• Device Emulation Environment on Windows 7

Oracle site some examples where you can use Java ME Embedded 8:

• Wireless modules
• Smart meters/smart sensors
• Industrial controllers
• Telehealth devices
• Environmental remote monitors
• Tracking systems
• Home automation devices
• Connected vending machines
• and general use cases where devices with local intelligence and versatile connectivity are required