Latest trends in database management


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Latest trends in database management

  1. 1. Latest Trends in Database Management by Prabath Kumarasinghe Senior Tech Lead at Ensiz PVT Ltd MSc in Web Technology (University of Southampton, UK) Bachelor of Computer Science(University of Colombo, SL)
  2. 2. Content 1 RDBMS 2 RDBMS Products 3 New trends in RDBMS
  3. 3. Content contd ... 4 NoSQL Databases 5 NoSQL Products 6 New trends in NoSQL Databases
  4. 4. Content contd ... 7 Cloud Databases 8 Cloud Products 9 New trends in Cloud Databases
  5. 5. Content contd ... 10 Graph Databases 11 Graph Products 12 New trends in Graph Databases
  6. 6. RDBMS Relational Database Management Systems Database Management Systems based on relational Model ● Firstly proposed by Edgar F. Codd in 1969. ● Contains tables with rows, columns and primary key. ● Maintain relationship between tables using foreign key. Query language is SQL ● SQL was one of the first commercial languages for Edgar F. Codd's relational model. ● SQL consists of a data definition language (DDL) and a data manipulation language (DML).
  7. 7. DDL and DML Data Definition Language (DDL) ● ● This is a sub set of SQL. SQL: CREATE, DROP, ALTER statements are coming under this definition. Data Manipulation Language (DML) ● As above this also sub set of SQL. ● Popular CRUD (Create, Read, Update, Delete) operations can be performed. ● SQL: INSERT, SELECT, UPDATE, DELETE statements are coming under this definition.
  8. 8. Transactions Database transactions ● ● Ensure some level data integrity and fault tolerance. Properties of database transaction are Atomicity, Consistency, Isolation and Durability (ACID). ACID ● Atomicity: Database operation either all occur or nothing occur. ● Consistency: Ensuring integrity constraints during database operations. ● Isolation: One operation become visible to other concurrent operations. ● Durability: Ensure transaction will survive permanently .
  9. 9. Database Normalization Database normalization ● Organizing the tables and fields to minimize the redundancy and dependency. ● This is a process of dividing large table into small tables with relations. ● Normalization concept are 1NF, 2NF, 3NF and BCNF (Boyce-Codd Normal Form) ● A relational database table is often described as "normalized", if it is in the Third Normal Form (3NF).
  10. 10. RDBMS Products RDBMS Products ● Oracle ● Microsoft SQL Server ● MySQL ● MariaDB ● PostgreSQL
  11. 11. Oracle Database History In 1977 Larry Ellison saw a IBM Journal of Research and Development, discovered a research paper that described a working prototype for a relational database management system (RDBMS). Showing it to coworkers Bob Miner and Ed Oates at Ampex . ● ● They started Software Development Company to build the Oracle, which was the first commercial SQL based RDBMS. MILSTONES ● 1978 Oracle version 1, written in assembly language. But Oracle verson 1 never released. ● 1979 Oracle Version2, was the first commercial SQL Relational Database Management System.
  12. 12. Oracle Database Contd ... MILSTONES ● 1983 Oracle version 3, written in C language. Is the first RDBMS to run on Mainframes, minicomputer and PCs. ● 1985 Oracle Version5, was the first RDBMS to support client-server environment. ● 1988 Oracle Version6, allow multiple users to work on single table, hot-backup reduce system maintenance, PL/SQL allow uses to process data while it remains in the database. ● 1992 Oracle Version7, with ground breaking functionality and several architectural changes. ● 1996 Oracle Version 7.3, to manage any type of data text, video, maps, sound, or images.
  13. 13. Oracle Database Contd ... MILSTONES ● 2001 Oracle version 9i, adds Oracle Real Application Clusters which allow customers to run their IT on connected low-cost servers, expanding performance, scalability and availability. ● 2003 Oracle Version 10g, the first grid computing product available for the enterprise. This allow to process the load based on demand. ● 2007 Oracle Version 11g, It's proven to be fast, reliable, secure and easy to manage for all types of database workloads including enterprise applications, data warehouses and big data analysis
  14. 14. Oracle Database Contd ... Oracle 11g features ● Lower IT Costs with Oracle Database 11g ● Storage management, memory management , statistics collection, backup and recovery, and SQL tuning have all been automated. ● Develop applications quickly as well ( All programming languages database drivers are fully integrate with Oracle 11g). ● Oracle Application Express (with limited programming knowledge user can build applications) . ● Maximum security and availability. ● Reduce the Hardware costs by a factor of 5X. ● Improve performance by a factor of 10x. ● Reduce storage costs by a factor of 10x.
  15. 15. Oracle Database Contd ... Oracle 11g features ● Database Consolidation Onto Private Clouds ● A private cloud is an efficient way to deliver database services because it enables IT departments to consolidate servers, storage, and database workloads onto a shared hardware and software. ● Business Drivers for consolidating databases onto a Private cloud ● A Consolidating databases onto a private cloud is typically done in one of two ways:Infrastructure Cloud or Database Cloud. ● Supports, building Private Cloud Infrastructures. ● There are many Oracle Technologies for consolidating databases on private clouds.
  16. 16. Oracle Database Contd ... Oracle 11g features ● Oracle: Big Data for the Enterprise ● Oracle Big Data Appliance : comes with full rack configuration with 18 Sun servers for a total storage capacity of 648TB. ● CDH and Cloudera Manager : CDH consists of 100% open source Apache Hadoop, Cloudera Manager is an end to end management application for CDH. ● Oracle Big Data Connectors : enables an integrated data set for analyzing all data. ● Oracle NoSQL Database : is a distributed, highly scalable, key value database based on Oracle Berkeley DB. ● In-Database Analytics: easy to use tools for in database, advanced analytics.
  17. 17. Microsoft SQL Server History ● In May 1989, Ashton-Tate/Microsoft SQL Server version 1.0 shipped. Press reviews were good, but sales lagged. Milestones ● 1989 - SQL Server 1.0 (16 bit) released. ● 1991 - SQL Server 1.1 (16 bit) released. ● 1993 - SQL Server 4.21 released. ● 1995 - SQL Server 6.0 released. ● 1996 - SQL Server 6.5 released. ● 1998 - SQL Server 7.0 (16 bit) released. ● 2000 - SQL Server 2000 released.
  18. 18. Microsoft SQL Server contd ... Milestones ● 2003 - SQL Server 2000 (64 bit Edition) released. ● 2005 - SQL Server 2005 released. ● 2008 - SQL Server 2008 released. ● 2010 - SQL Azure DB released (Cloud database). ● 2010 - SQL Server 2008 R2 released. ● 2012 - SQL Server 2012 released. SQL Server 2012 ● SQL Server 2012 will provide Mission Critical Confidence with greater uptime, blazing-fast performance and enhanced security features for mission critical workloads; Breakthrough Insight with managed self-service data exploration and stunning interactive data visualizations capabilities
  19. 19. Microsoft SQL Server contd ... SQL Server 2012 ● Manage data of any type or size : able to manages data of any type, whether structured or unstructured, and of any size – from gigabytes to petabytes. ● Enrich your data with the worlds data : By connecting to external data sources like U.S. Census Bureau, United Nations, etc .. user can begin to answer new types of questions and deliver new value in ways that previously were not possible. ● Gain insight from any data : deliver new insights from all types of data- structured, unstructured, previously archived or discarded.
  20. 20. MySQL MySQL ● ● The worlds most popular open source database. Original development of MySQL by Michael Widenius and David Axmark beginning in 1994. Milestones ● 1996 – MySQL version 3.19 released. ● 1997 – MySQL version 3.21 released. ● 1998 – MySQL version 3.22 released. ● 2000 – MySQL version 3.23 released. ● 2002 – MySQL version 4.0 released. ● 2003 – MySQL version 4.01 released. ● 2004 – MySQL version 4.1 released.
  21. 21. MySQL Milestones ● 2005 – MySQL version 5.0 released. ● Sun Microsystems acquired MySQL in 2008. ● 2008 – MySQL version 5.1 released. ● Oracle acquired Sun Microsystems on 27 January 2010. ● 2010 – MySQL version 5.5 released. ● 2011 – MySQL version 5.6 released. MySQL 5.6 ● MySQL 5.6 is the best release ever of the world's most popular open source database and provides a new, advanced feature set designed to enable those who are building the next generation of web-based and embedded applications and services.
  22. 22. MySQL MySQL 5.6 ● Better Performance and Scalability. ● Improved better transactional throughput. ● Improved Optimizer for better query execution times and diagnostics. ● Better Application Availability. ● Better Developer Support. ● Improved Replication for high performance and self-healing cluster deployments. ● Improved Performance Schema for better instrumentation and monitoring. ● Improved Security for worry-free application deployments and other important enhancements.
  23. 23. MariaDB MariaDB ● Database server developed by some of the original authors of MySQL, offers drop-in replacement functionality. ● Its lead developer is Michael Widenius, the founder of MySQL and Monty Program AB Milestones ● 2009 – MariaDB version 5.1 released. ● 2010 – MariaDB version 5.2 released. ● 2011 – MariaDB version 5.3 released. ● 2012 – MariaDB version 5.5 released. ● 2012 – MariaDB version 10.0.0 alpha released.
  24. 24. MariaDB contd …. MariaDB 5.5 vs MySQL 5.6 ● More Storage Engines than MySQL. ● Speed improved compared to MySQL. ● Extensions & new features. ● Microseconds in MariaDB . ● GIS Functionality, etc .. ● Better Testing. ● Fewer warnings and bugs. ● Truly Open Source.
  25. 25. PostgreSQL PostgreSQL ● The world most advance open source Database Management System. ● is ACID-compliant, is fully transactional and has extensible data types, operators, index methods, functions, aggregates, procedural languages, and has a large number of extensions written by third parties. Milestones ● 1996 – PostgreSQL version 1.0 released. ● 1997 – PostgreSQL version 6.0 released. ● 2000 – PostgreSQL version 7.0 released. ● 2005 – PostgreSQL version 8.0 released. ● 2010 – PostgreSQL version 9.0 released.
  26. 26. PostgreSQL PostgreSQL 9.0 ● PostgreSQL is a powerful, open source object-relational database system. It has more than 15 years of active development and a proven architecture that has earned it a strong reputation for reliability, data integrity, and correctness. ● Support nested transactions. ● It supports international character sets. ● It is highly scalable both in quantity of data it can manage and in the number of concurrent users it can accommodate. ● PostgreSQL, allowing it to be used as a spatial database for geographic information systems (GIS).
  27. 27. NoSQL Databases NoSQL Databases ● A NoSQL database provides a mechanism for storage and retrieval of data that use looser consistency models than traditional relational databases in order to achieve horizontal scaling and higher availability. In short, NoSQL database management systems are useful when ● working with a huge quantity of data (especially big data) when the data's nature does not require a relational model. The data can be structured, but NoSQL is used when what really ● matters is the ability to store and retrieve great quantities of data, not the relationships between the elements. NoSQL cannot necessarily give full ACID guarantees. ●
  28. 28. NoSQL Databases continued. Advantages in NoSQL ● Elastic scaling : they’re usually designed with low-cost commodity hardware in mind therefore scaling easy to handle. ● Big data: Today, the volumes of “big data” that can be handled by NoSQL systems, such as Hadoop, outstrip what can be handled by the biggest RDBMS. ● Goodbye DBA : NoSQL databases are generally designed from the ground up to require less management: automatic repair, data distribution, and simpler data models lead to lower administration. ● Economics : NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes, while RDBMS tends to rely on expensive proprietary servers and storage systems. ● Flexible data models : NoSQL databases have far more relaxed or even nonexistent data model restrictions.
  29. 29. NoSQL Databases continued. Challenges in NoSQL ● Maturity : RDBMS systems have been around for a long time. The maturity of the RDBMS is reassuring. In NoSQL many key features yet to be implemented. ● Support : In contrast, most NoSQL systems are open source projects, and although there are usually one or more firms offering support for each NoSQL database. ● Analytics and business intelligence :NoSQL databases offer few facilities for ad-hoc query and analysis. Even a simple query requires significant programming expertise. ● Administration : NoSQL today requires a lot of skill to install and a lot of effort to maintain. ● Expertise : There are literally millions of developers throughout the world, and in every business segment, who are familiar with RDBMS concepts and programming. almost every NoSQL developer is in a learning mode.
  30. 30. NoSQL Database Products NoSQL Database Products ● MongoDB ● CouchDB ● Oracle NoSQL Database ● OrientDB ● Apache Cassandra
  31. 31. MongoDB MongoDB ● MongoDB (from "humongous") is an open source document-oriented database system developed and supported by 10gen. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational ● database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster. ● 10gen began development of MongoDB in October 2007. The database is used by MTV Networks, Foursquare, UIDA etc... MongoDB is the most popular NoSQL database management system.
  32. 32. MongoDB contd ... Example of MongoDB Document { "_id": ObjectId("4efa8d2b7d284dad101e4bc9"), "Last Name": "DUMONT", "First Name": "Jean", "Date of Birth": "01-22-1963" }, { "_id": ObjectId("4efa8d2b7d284dad101e4bc7"), "Last Name": "PELLERIN", "First Name": "Franck", "Date of Birth": "09-19-1983", "Address": "1 chemin des Loges", "City": "VERSAILLES" }
  33. 33. MongoDB contd …. MongoDB features ● Document-Oriented Storage. ● Full Index Support. ● Replication & High Availability. ● Querying. ● Advanced security ● Professional Support by 10gen.
  34. 34. MongoDB contd …. MongoDB FAQs ● What kind of database is MongoDB? ● ● MongoDB is a document-oriented DBMS. Do MongoDB databases have tables?. ● Instead of tables, a MongoDB database stores its data in collections. ● Does MongoDB support SQL? ● No ● However, MongoDB does support a rich, ad-hoc query language of its own.
  35. 35. MongoDB contd …. MongoDB FAQs ● What are typical uses for MongoDB? ● MongoDB has a general-purpose design, making it appropriate for a large number of use cases. Examples include content management systems, mobile applications, gaming, e-commerce, analytics, archiving, and logging. ● Do not use MongoDB for systems that require SQL, joins, and multi-object transactions. ● Does MongoDB support transactions? ● MongoDB does not provide ACID transactions. ● However, MongoDB does provide some basic transactional capabilities. Some Atomic operations are possible. ● Additionally, you can make writes in MongoDB durable (the ‘D’ in ACID).
  36. 36. CouchDB CouchDB ● Apache CouchDB, commonly referred to as CouchDB, is an open source database that focuses on ease of use and on being "a database that completely embraces the web". It is a NoSQL database that uses JSON to store data, JavaScript as its query language. ● CouchDB was first released in 2005 and later became an Apache project in 2008. ● Unlike in a relational database, CouchDB does not store data and relationships in tables. Instead, each database is a collection of independent documents.
  37. 37. CouchDB contd …. CouchDB features ● Document Storage. ● ACID Semantics. ● Security and Validation. ● Distributed Updates and Replication.
  38. 38. CouchDB contd …. CouchDB features ● Document Storage. ● ACID Semantics. ● Security and Validation. ● Distributed Updates and Replication.
  39. 39. Oracle NoSQL Database Oracle NoSQL Database ● The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable and available data storage across a configurable set of systems that function as storage nodes. ● Data is stored as key-value pairs, which are written to particular storage node(s). ● Oracle’s NoSQL Database brings enterprise quality storage and performance to the highly available, widely distributed NoSQL environment. Its commercially proven, write optimized storage system delivers outstanding performance as well as robustness and reliability, and its “No Single Point of Failure” design ensures that the system continues to run and data remain available after any failure.
  40. 40. OrientDB OrientDB ● OrientDB is an open source NoSQL database management system written in Java. Even if it is a document-based database, the relationships are managed as in graph databases with direct connections between records. ● it's amazing fast: can store up to 150,000 records per second on common hardware. ● Supports advanced features such as ACID Transactions, Fast Indexes, Native and SQL queries. It imports and exports documents in JSON.
  41. 41. OrientDB contd ... OrientDB features ● Transactional: supports ACID Transactions. On crash it recovers pending documents. ● ● GraphDB: native management of graphs.. SQL: supports SQL language with extensions to handle relationships without SQL join, manage trees and graphs of connected documents. ● Web ready: supports natively HTTP, RESTful protocol and JSON without use 3rd party libraries and components. ● Run everywhere: the engine is 100% pure Java: runs on Linux, Windows and any system that supports Java technology.
  42. 42. Apache Cassandra Apache Cassandra ● Apache Cassandra is an open source distributed database management system. It is an Apache Software Foundation top-level project designed to handle very large amounts of data spread out across many commodity servers while providing a highly available service with no single point of failure. ● It is a NoSQL solution that was initially developed by Facebook and powered their Inbox Search feature until late 2010. ● It was released as an open source project on Google code in July 2008. In March 2009, it became an Apache Incubator project. On February 17, 2010 it graduated to a top-level project.
  43. 43. Apache Cassandra contd ... Apache Cassandra Features ● Fault Tolerant : Data is automatically replicated to multiple nodes for fault-tolerance. ● Performant : Cassandra consistently outperforms popular NoSQL alternatives. ● Decentralized : There are no single points of failure. There are no network bottlenecks. Every node in the cluster is identical. ● Durable : Cassandra is suitable for applications that can't afford to lose data, even when an entire data center goes down. ● Professionally Supported : Cassandra support contracts and services are available from third parties.
  44. 44. Cloud Databases Cloud Databases ● A cloud database is a database that typically runs on a cloud computing platform ( a large number of computers that are connected through a real-time communication network, typically the Internet) . ● While a cloud database can be a traditional database such as a MySQL or SQL Server database that has been adopted for cloud use. ● Cloud databases can offer significant advantages over their traditional counterparts, including increased accessibility, automatic fail-over and fast automated recovery from failures, automated on-the-go scaling, minimal investment and maintenance of in-house hardware, and potentially better performance.
  45. 45. Cloud Databases contd ... Cloud Databases ● Databases in multiple departments of a large company, for example, can be combined in the cloud into a single hosted (CDBMS) . ● The ability to pay for storage capacity and bandwidth on a per-use model. ● The ability to move the database from one location to another. ● Ability to choose the DBMS type whether it is RDMBS or NoSQL. ● At the same time, cloud databases have their share of potential drawbacks, including security and privacy issues as well as the potential loss of or inability to access critical data in the event of a disaster of the cloud database service provider.
  46. 46. Cloud Databases Products Cloud Database Products ● Rackspace Cloud Databases ● Amazon Cloud Databases ● Google Cloud SQL ● MongoLab ● Oracle Cloud
  47. 47. Rackspace Rackspace ● The high performance MySQL database on the cloud Deliver faster applications on the first relational database service built on OpenStack. ● Deliver faster applications : The Cloud Databases architecture is built for high and consistent performance, high performance, dedicated storage network. ● Add more value to your team: Easily provision your database via an API or the Control Panel, and save time through automation of time-consuming tasks such as deployment, configuration, and patching. You can also easily scale your database for bigger or smaller memory sizes.
  48. 48. Rackspace contd ... Rackspace ● Protect your data : Deliver more reliable applications and minimize data loss. Our service includes redundant storage to protect your data against hardware failures. ● Count on us for Fanatical Support : When you choose a managed cloud account, we'll help you move your databases and tables, create users, backup or restore your database, and help you with basic optimizations. ● Speedy delivery of your data : Rackspace Cloud Databases provides fast, scalable, fully managed hosting for your MySQL instances.
  49. 49. Amazon Cloud Databases Amazon Cloud Databases ● Also called Amazon Relational Database Service (Amazon RDS), which allows, easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks, freeing you up to focus on your applications and business. ● Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. ● As with all Amazon Web Services, there are no up-front investments required, and you pay only for the resources you use.
  50. 50. Amazon Cloud Databases contd ... Amazon Cloud Databases features ● Pre-configured Parameters – Amazon RDS DB Instances are pre-configured with an appropriate set of parameters and settings appropriate for the DB Instance class you have selected. ● Monitoring and Metrics - user can use the AWS Management Console to view key operational metrics for your DB Instance deployments, including compute/memory/storage capacity utilization, I/O activity, and DB Instance connections. ● Automated Backups - Turned on by default, the automated backup feature of Amazon RDS enables point-in-time recovery for your DB Instance.
  51. 51. Amazon Cloud Databases contd ... Amazon Cloud Databases features ● DB Snapshots – DB Snapshots are user-initiated backups of your DB Instance. ● Push-Button Scaling – Using the Amazon RDS APIs or with a few clicks on the AWS Management Console, you can scale the compute and memory resources powering your deployment up or down. ● On-Demand DB Instances - On-Demand DB Instances let you pay for compute capacity by the hour your DB Instance runs with no long-term commitments. ● Security – you can configure firewall settings and control network access to your DB Instances..
  52. 52. Amazon Cloud Databases contd ... Amazon Cloud Databases features ● DB Snapshots – DB Snapshots are user-initiated backups of your DB Instance. ● Push-Button Scaling – Using the Amazon RDS APIs or with a few clicks on the AWS Management Console, you can scale the compute and memory resources powering your deployment up or down. ● On-Demand DB Instances - On-Demand DB Instances let you pay for compute capacity by the hour your DB Instance runs with no long-term commitments. ● Security – you can configure firewall settings and control network access to your DB Instances..
  53. 53. Google Cloud SQL Google Cloud SQL ● Google Cloud SQL is a web service that allows you to create, configure, and use relational databases that live in Google's cloud. It is a fully-managed service that maintains, manages, and administers your databases, allowing you to focus on your applications and services. ● By offering the capabilities of a familiar MySQL database, the service enables you to easily move your data, applications, and services in and out of the cloud. This enables high data portability and helps you achieve faster time-to-market because you can quickly leverage your existing database. ● You only pay for your instance while it is being accessed.
  54. 54. Google Cloud SQL contd .. Google Cloud SQL features ● Easy to use : A graphical user interface allows you to create, configure, manage, and monitor your database instances, with just a click. ● Fully managed : No worrying about tasks such as replication, patch management, or backups. These are all taken care of. ● Highly Available : Features like automatic replication across multiple geographic regions are built in, so the service is available, and your data is preserved, even if a datacenter becomes unavailable. ● Exceptional Security: Google provides cloud services in a manner drawn from its experience with operating its own business, as well as its core services like Google Search.
  55. 55. MongoLab MongoLab ● The magic of the cloud : Create and scale databases on-demand on all the major cloud providers. ● Total data protection: Sleep well knowing that we replicate, backup, and redundantly archive every database. ● Max uptime & performance: Our experienced robots and experts continuously monitor and manage your databases. ● Expert care and support : Thoughtful, timely support from real developers is why customers love us.
  56. 56. Oracle Cloud Oracle Cloud ● The Oracle Database you love, now in the cloud. ● Easy : Self-service management enables almost instantaneous provisioning of environments. ● Standards-Based : SQL support with access through RESTful Web Services. ● Enterprise-Grade : Enterprise security, reliability, and performance to support business-critical applications. ● Simple Pricing : Simple, predictable pricing ($175 / Month, lowest plan).
  57. 57. Graph Databases Graph Databases ● A graph database is a database that uses graph structures with nodes, edges, and properties to represent and store data.
  58. 58. Graph Databases contd ... Graph Databases ● Nodes represent entities such as people, businesses, accounts, or any other item you might want to keep track of. ● Properties are pertinent information that relate to nodes or edges. ● Edges are the lines that connect nodes to nodes and they represent the relationship between the two. ● Compared with relational databases, graph databases are often faster for associative data sets. ● They can scale more naturally to large data sets as they do not typically require expensive join operations.
  59. 59. Graph Database Products Graph Database Products ● Neo4j ● OrientDB ● HyperGraphDB ● Titan ● GraphBase
  60. 60. Neo4j Neo4j ● Neo4j is an open-source, high-performance, enterprise-grade NOSQL graph database. ● Neo4j is a robust (fully ACID) transactional graph database. ● Durable and fast. ● Massively scalable, up to several billio nodes/relationships/properties ● Highly-available, when distributed across multiple machines. ● Expressive, with a powerful, human readable graph query language.
  61. 61. HyperGraphDB HyperGraphDB ● HyperGraphDB is a general purpose, open-source data storage mechanism based on a powerful knowledge management formalism known as directed hypergraphs. ● Graph-oriented storage. ● Graph traversals and relational-style queries. ● Customizable storage management. ● Fully transactional.
  62. 62. Titan Titan ● Titan is a highly scalable graph database optimized for storing and querying massive-scale graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. ● Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals. ● Elastic and linear scalability for a growing data and user base. ● Data distribution and replication for performance and fault tolerance. ● Support for ACID. ● Support for full-text search.
  63. 63. GraphBase GraphBase ● GraphBase is a second generation Graph Database Management System (DBMS). Built for 21st Century data problems, GraphBase is a game-changer when it comes to handling large, complex data structures. ● GraphBase makes massive, highly-structured data stores possible because it was built from scratch to manage large graphs. ● Tiny memory and storage footprint. ● Built-in support for traversal ● Graph-based transactions.
  64. 64. Thank you !