DBMS > Amazon Neptune vs. Microsoft Access vs. Realm vs. Spark SQL vs. Tarantool
System Properties Comparison Amazon Neptune vs. Microsoft Access vs. Realm vs. Spark SQL vs. Tarantool
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Amazon Neptune Xexclude from comparison | Microsoft Access Xexclude from comparison | Realm Xexclude from comparison | Spark SQL Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, reliable graph database built for the cloud | Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.) | A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data | Spark SQL is a component on top of 'Spark Core' for structured data processing | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Relational DBMS | Document store | Relational DBMS | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS with Tarantool/GIS extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/neptune | www.microsoft.com/en-us/microsoft-365/access | realm.io | spark.apache.org/sql | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/neptune/developer-resources | developer.microsoft.com/en-us/access | realm.io/docs | spark.apache.org/docs/latest/sql-programming-guide.html | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Microsoft | Realm, acquired by MongoDB in May 2019 | Apache Software Foundation | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2017 | 1992 | 2014 | 2014 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1902 (16.0.11328.20222), March 2019 | 3.5.0 ( 2.13), September 2023 | 2.10.0, May 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial Bundled with Microsoft Office | Open Source | Open Source Apache 2.0 | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | Scala | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Windows Not a real database server, but making use of DLLs | Android Backend: server-less iOS Windows | Linux OS X Windows | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | yes | yes | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | string, double, decimal, uuid, integer, blob, boolean, datetime | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | yes but not compliant to any SQL standard | no | SQL-like DML and DDL statements | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | OpenCypher RDF 1.1 / SPARQL 1.1 TinkerPop Gremlin | ADO.NET DAO ODBC OLE DB | JDBC ODBC | Open binary protocol | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Go Java JavaScript PHP Python Ruby Scala | C C# C++ Delphi Java (JDBC-ODBC) VBA Visual Basic.NET | .Net Java with Android only Objective-C React Native Swift | Java Python R Scala | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes since Access 2010 using the ACE-engine | no runs within the applications so server-side scripts are unnecessary | no | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes since Access 2010 using the ACE-engine | yes Change Listeners | no | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | none | none | yes, utilizing Spark Core | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances. | none | none | none | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in graphs | yes | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID but no files for transaction logging | ACID | no | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, cooperative multitasking | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes with encyption-at-rest | yes but no files for transaction logging | yes | yes | yes, write ahead logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes In-Memory realm | no | yes, full featured in-memory storage engine with persistence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | no a simple user-level security was built in till version Access 2003 | yes | no | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Neptune | Microsoft Access | Realm | Spark SQL | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | MS Access drops in DB-Engines Ranking Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking New DB-Engines Ranking shows the popularity of database management systems | MySQL, PostgreSQL and Redis are the winners of the March ranking | Data processing speed and reliability: in-memory synchronous replication Find and link similar entities in a knowledge graph using Amazon Neptune, Part 1: Full-text search | Amazon Web ... Find and link similar entities in a knowledge graph using Amazon Neptune, Part 2: Vector similarity search | Amazon ... Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ... Create a Virtual Knowledge Graph with Amazon Neptune and an Amazon S3 data lake | Amazon Web Services Uncover hidden connections in unstructured financial data with Amazon Bedrock and Amazon Neptune | Amazon Web ... provided by Google News Abusing Microsoft Access "Linked Table" Feature to Perform NTLM Forced Authentication Attacks Hackers Exploit Microsoft Access Feature to Steal Windows User’s NTLM Tokens MS access program to increase awareness and independence of those living with MS and disability After installing Navisworks, Office 2016 (32-bit) applications stopped launching How to Connect MS Access to MySQL via ODBC Driver provided by Google News MongoDB aims to unify developer experience with launch of MongoDB Cloud Danish CEO explains Silicon Valley learning curve for European entrepreneurs - San Francisco Business Times Here are the winners of Nordic Startup Awards Is Swift the Future of Server-side Development? Kotlin Programming Language Will Surpass Java On Android Next Year provided by Google News Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services What is Apache Spark? The big data platform that crushed Hadoop Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024 Performant IPv4 Range Spark Joins | by Jean-Claude Cote 18 Top Big Data Tools and Technologies to Know About in 2024 provided by Google News Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities Deploying Tarantool Cartridge applications with zero effort (Part 1) Deploying Tarantool Cartridge applications with zero effort (Part 2) Тarantool Cartridge: Sharding Lua Backend in Three Lines VShard — horizontal scaling in Tarantool provided by Google News |
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