Datacenter replication solution with quasardb

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1 Datacenter replication solution with quasardb Technical positioning paper April 2017 Release v1.3 Contact: Quasardb A datacenter survival guide quasardb

2 INTRODUCTION 1 KEY DATACENTER CONCEPTS AND QUASARDB DATA MANAGEMENT TECHNIQUES 2 DATA PERSISTENCE 2 DATA REPLICATION 2 AUTOMATIC LOAD BALANCING 2 HOW TO IMPLEMENT QUASARDB IN A DATACENTER WITHIN THE COMPANY MAN NETWORK 3 SCENARIO 3 SOLUTION 3 BENEFITS 3 POINTS OF ATTENTION 4 BEST PRACTICE 5 NO DATA REPLICATION 5 DATA REPLICATION SET TO 1 6 DATA REPLICATION SET TO 2 7 HOW TO IMPLEMENT QUASARDB LEVERAGING CLOUD BASED INFRASTRUCTURE 8 SCENARIO 8 DESCRIPTION 8 HOW DOES CROSS DATACENTER REPLICATION (XCR) WORK? 9 BENEFITS 10 POINT OF ATTENTION 10 HOW TO IMPLEMENT QUASARDB ACROSS A DATACENTER WITHIN THE COMPANY WAN NETWORK 11 SCENARIO 11 DESCRIPTION 11 BENEFITS 11 POINT OF ATTENTION 12 CONCLUSION 13 Quasardb A datacenter survival guide quasardb

3 Introduction Data is the new oil and data availability is paramount. Managing data successfully is a significant challenge for today s businesses. Most of today s successful companies operate in more than one location, many even globally, and data replication (and recovery) across datacenters is a challenge for both the business and technology teams. Datacenters are emerging all over the world and require a full range of multi-datacenter management tools to ensure data is available all the time, in different time zones, and persisted (stored) appropriately for immediate access (including fast and automated recovery from planned or unplanned outage(s)). As an example - one of the leading investment banks in Paris requires the data that is produced in Paris to be replicated to its Tokyo and New York offices in order to ensure trade consistency across the organisation. Similarly, data in the Tokyo and New York offices needs to be available to the Paris office. To enable this, quasardb implemented the quasardb XCR module (a cross-cluster replication module) to federate the bank s cached data asynchronously across multiple geographically dispersed clusters servicing Paris, Tokyo and New York. This enabled the cached data to be federated across all the clusters and provided multiple points of access for application users in different geographical locations, redundancy and off-site backup. This is a typical scenario and experienced by many firms large or small. If not managed correctly, data may be out-of-date, incomplete or even missing; the result of which can be critical to business operations. This paper describes relevant concepts of data management and a variety of ways in which to manage the datacenters successfully. Quasardb A datacenter survival guide quasardb 1

4 Key datacenter concepts and quasardb data management techniques Data persistence Persistence is the continuance of an effect after its cause is removed. In other words, for a data store to be considered persistent, it must write to non-volatile storage. All data stored in quasardb is persisted and all write queries are automatically load-balanced. Quasardb also provides a Transient mode to be enabled in which case, it operates as a pure in-memory distributed data grid. Data replication Data replication is the frequent electronic copying of data from a source in one computer or server to a replica in another so that all users share the same level of information. Technically, it is the process of duplicating entries across multiple nodes and is particularly important for fault tolerance to maintain functionality in the event of a system failure. Data replication greatly reduces the odds of functional failures but comes at the cost of increased disk storage and memory usage, as well as a reduction in performance when adding or updating entries. In quasardb, data is replicated on nodes and its successors, and can be configured in a number of ways for maximum efficiency. To explain - using a factor-two replication method, an entry will be stored on its primary node and on that node s successor. With a factor-three replication, an entry will be stored on its primary node and on its two following successors. This level of configuration enables firms to create a system to support different levels of system failures that could compromise data availability. Replication is done synchronously as data is added or updated. The call will not successfully return until the data has been stored and fully replicated across the appropriate nodes. When a node fails or when entries are otherwise unavailable, client requests will be served by the successor nodes containing the duplicate data. For an entry to become unavailable, all nodes containing the duplicate data need to fail simultaneously. For more information, see Impact on reliability Automatic load balancing Automatic load balancing is the ability for a system to serve multiple concurrent activities transparently. In the context of data, it provides the ability to automatically dispatch read/write requests across many nodes to alleviate performance issues. As of quasardb 1.2.0, if the cluster uses Data replication, read queries are automatically loadbalanced. Nodes containing replicated entries may respond instead of the original node to provide faster lookup speed. Data locality is implemented to support local lookup vs cross network support (IP netmask is used). Quasardb A datacenter survival guide quasardb 2

5 How to implement quasardb in a datacenter within the company MAN network A metropolitan area network (MAN) is a computer network that interconnects users with computer resources in a geographic area or region larger than that covered by even a large local area network (LAN) but smaller than the area covered by a wide area network (WAN). Scenario The company wishes to implement a reliable and performant enterprise data grid within its MAN. Two or more datacenters are connected to a high speed, low latency and high throughput network. Solution This scenario, joining two datacenters, demonstrates how a single logical quasardb cluster is used to span the entire MAN. It behaves the same way as a single-datacenter quasardb cluster. The behaviour is similar and there are no configuration deviations whatsoever. Benefits This configuration allows a customer to implement its MAN-wide data grid infrastructure in a simple way. It provides all the benefits one can expect from a single quasardb cluster (i.e. performance, data access and simplicity). It is achieved using the standard quasardb data persistence and replication mechanisms. ( Quasardb A datacenter survival guide quasardb 3

6 The read/write operations from/to the quasardb cluster are automatically load balanced across all the nodes in the logical cluster to avoid cross datacenter traffic when not required which could lead to performance degradation. Points of attention One should pay extra care to the network design. Quasardb will easily take advantage of the bandwidth. When enabling replication (for additional availability), this will increase the amount of data shuffled across the MAN. If you enable replication with two copies of the data, the net capacity of your cluster will be divided by two. A single client/quasardb write ops will lead to two cluster writes. In a quasardb cluster, every node may need, at some point, to speak to any other node. Therefore, if you have a firewall on your MAN, a rule must be created to allow this dialog to take place. The port is fixed and can be configured if required (2836 by default). If you have a firewall within your MAN, it means that if you have a M nodes cluster in Datacenter 1, and N nodes cluster in Datacenter 2, you will need to have M*N ports opened in your firewall (defined port for quasardb, can be changed upon configuration). Quasardb A datacenter survival guide quasardb 4

7 Best practice No data replication In this scenario, no data replication is carried out by the cluster. Clients access any part of the logical cluster to write its data in a parallel way. If the cluster loses one of its nodes, data access cannot be guaranteed. Quasardb does not recommend this scenario except when using quasardb as a pure inmemory data grid. Quasardb A datacenter survival guide quasardb 5

8 Data replication set to 1 In this scenario, quasardb will create one copy for each data block being sent by the clients. Each write will be duplicated to the next node and transaction will only be acknowledged when both copies are committed by the system. Please note that quasardb implements three different write strategies (per logical cluster): 1. disk+sync maximum reliability with significant performance penalty (all buffers are explicitly flushed for every write) 2. disk (default) quasardb waits for the write acknowledgement but does not flush the system cache 3. asynchronous data is stored in a buffer that will be later written and flushed to disk Quasardb A datacenter survival guide quasardb 6

9 Data replication set to 2 In this scenario, quasardb will create two copies for each data block being sent by the client. Each write will be duplicated to the next two nodes and transactions will only be acknowledged when both copies are committed by the system. The user can still choose amongst the three different write strategies. Quasardb A datacenter survival guide quasardb 7

10 How to implement quasardb leveraging Cloud based infrastructure Scenario This scenario is an extension of the previous scenario. The customer decides to leverage a Cloud based solution to create a new quasardb cluster. This cluster can be used as a backup cluster, or to support a new Cloud based application or to expand the capacity of the nominal cluster for testing or to support workload peak. Description In this scenario, we use the cross-cluster replication module (XCR) of quasardb. The XCR module supports asynchronous cluster-to-cluster replication (i.e. all the data stored in the cluster) and will replicate all the content of a source cluster to a destination cluster. The source cluster and the destination cluster can have different configuration and hardware layouts; however, the destination cluster must have sufficient space to hold all the data that will be sent by the source cluster. There are two scenarios to consider: 1. ACTIVE/PASSIVE The quasardb cluster in Datacenter 1 is the Master in the relationship. All the data modified in the Master quasardb cluster will be pushed asynchronously to the Slave(s) quasardb clusters. No data should be changed on the Slave cluster(s) as they could be overwritten by the Master updates. If the Master quasardb cluster is unavailable, replication will not take place. Updates on the Slave cluster, should they occur, will not be accounted for by the Master cluster. Suggested use cases: offline backup, make data available in remote clusters (Read-only), 2. ACTIVE/ACTIVE Two clusters can be mutually source and destination clusters, resulting in active/active replication. As the replication is cluster-wide (in the current release of XCR), it could lead to data inconsistencies if two clients are updating data in both quasardb clusters. However, in this configuration the user must understand that simultaneous update of the same entries on the two clusters can result in inconsistencies as replication is asynchronous. Suggested use cases: High-availability environment where continuous access is necessary, zero downtime transactional system. The XCR module does not require any additional software modules to be installed. Configuration is carried out on a cluster basis. Quasardb A datacenter survival guide quasardb 8

11 How does cross datacenter replication (XCR) work? In the configuration file, the user specifies a destination cluster, a maximum wait interval and a maximum journal size. Each node within the source cluster is responsible for a persisted journal of recently modified entries and will push these modifications to the appropriate nodes of the destination cluster when either: The journal has reached its maximum configurable length or When the wait interval has reached its maximum duration Once replication is complete, the journal is emptied. Communication between the nodes is compressed for optimal data transfer. If the destination cluster is not available, the node will log an error and attempt to replicate again later. In case of network split (aka, split brain) in Active/Active mode, each cluster will keep operating in standalone mode. Once the network connectivity is resumed, by default, each cluster will push its data updates to the other replica. Versioning (MVCC) will guarantee that all transactions will be stored. However, if the network split lasts longer than a configurable timer, there will be no automatic data updates between the clusters. A manual intervention will be required to re-enable the replication. The data channel can be secured by utilising a dedicated user for replication, using the integrated security authentication of quasardb. Quasardb A datacenter survival guide quasardb 9

12 Benefits This setup requires the optional XCR quasardb module. A monitoring console will be added in quasardb v3.0 (2018). Quasardb is available on Amazon AWS and Microsoft Azure marketplace. An additional Cloud platform will be made available upon demand. This will allow customers to implement hybrid based infrastructures. All data transfer mechanisms required to transport data from the customer datacenter to the Cloud provider are done at the data layer. This is fully asynchronous and can survive network glitches. Point of attention The connectivity between the Cloud provider s network and the customer s datacenter is paramount. The quasardb XCR module leverages the underlying quasardb data replication mechanisms. It can accommodate transient network failure. If the connectivity is unavailable for a longer period, quasardb will automatically resynchronize once the network is back and nodes can communicate again. The XCR module is firewall friendly but all cluster nodes need to be able to speak to each other. In this case, it means that if you have M nodes cluster in premise, and N nodes cluster in the Cloud provider s datacenter, you will need to have M*N ports opened in your firewall (defined port for quasardb, can be changed upon configuration). Quasardb A datacenter survival guide quasardb 10

13 How to implement quasardb across a datacenter within the company WAN network Scenario The company wishes to implement a reliable and performant enterprise data grid within its Wide Area Network (WAN). Two or more datacenters are connected to a network that can span across multiple time zones and geographies. Data needs to be replicated across and accessible within seconds. Description In this scenario, we will implement a quasardb cluster per datacenter (or region) and enable the XCR quasardb module (optional). This scenario is like the previous one. Therefore, all points of interest are to be considered carefully. Benefits This module will allow customers to implement federated quasardb clusters in a simple way. This will allow customers to replicate data spaces across various geographies. Quasardb A datacenter survival guide quasardb 11

14 Point of attention The network is paramount. The XCR module leverages the underlying quasardb data replication mechanisms. It can accommodate transient network failure. If the connectivity is unavailable for a longer period, quasardb will automatically resynchronize once the network is back and nodes can discuss together. The XCR module is firewall friendly but all cluster nodes need to be able to speak to each other. In this case, it means that if you have a M nodes cluster in premise, and N nodes cluster in the cloud provider datacenter, you will need to have M*N ports opened in your firewall (defined port for quasardb, can be changed upon configuration). Quasardb A datacenter survival guide quasardb 12

15 CONCLUSION Quasardb is a high-performance, distributed, column-oriented database with native time series support. Transfers, computations and aggregations are so fast that analysts can work interactively on their data, regardless of the amount stored. First class performance: never wait on the database with millions of requests per second per node Direct to data approach for easy integration with the existing applications (Microsoft Excel, ActivePivot, Apache Spark...) or through our API Transparent scaling to accommodate growth At the heart of quasardb is a unique distributed key-value store technology. It scales horizontally and vertically for virtually unlimited capabilities. All of this, without any compromise regarding reliability and consistency. Peer-to-peer distribution based on the Chord algorithm Lockfree and multithreaded code for vertical scaling Implementation in modern C++ for maximum efficiency You can store raw data of any form and size into quasardb, and you can work your on time series with native operations. Quasardb takes away all the hard problems such as concurrent access, reliable distribution, reduction, and efficient operations. Time series, and data structures scale transparently and automatically across the cluster All operations are atomic, durable and consistent by default Billions of rows per second per core aggregation speed (using SSE4.2 and AVX2) How to manipulate several entries at once in a consistent fashion? Quasardb comes out of the box with distributed transactions. Transactions enable you to execute commands on several entries in a safe, predictable, consistent manner. Distributed transactions based on Multi Version Concurrency Control (MVCC) Unlimited read scalability No global lock: transactions can work in parallel on different entries How to find your entry when you don t have its key? The typical solution is to create a schema and perform queries based on this schema. Quasardb has a better, schema-less approach: tags. Tags are extremely fast and scale automatically. Don t compromise between search and speed: just tag! Distributed tags for flexible data management Immediate tag-based lookup Tags can be removed or renamed Quasardb A datacenter survival guide quasardb 13

16 Quasardb is write-safe by default and offers features to sync absolutely everything you do for maximum safety. Thanks to its master-less design, quasardb is able to face the loss of nodes transparently. When a node joins back, quasardb will replay the log of events to guarantee consistency. Fault-tolerant by design: perfectly symmetric peer-to-peer architecture Safe by default MVCC, high-resolution timestamps and the Chord algorithm are used together to guarantee consistency Our community edition is fully featured and without any time limit.. Visit our website at Quasardb A datacenter survival guide quasardb 14

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