DBMS > Amazon Neptune vs. Apache Druid vs. Apache Kylin vs. Google Cloud Spanner vs. PostgreSQL
System Properties Comparison Amazon Neptune vs. Apache Druid vs. Apache Kylin vs. Google Cloud Spanner vs. PostgreSQL
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Name | Amazon Neptune Xexclude from comparison | Apache Druid Xexclude from comparison | Apache Kylin Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, reliable graph database built for the cloud | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack | A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Relational DBMS Time Series DBMS | Relational DBMS | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/neptune | druid.apache.org | kylin.apache.org | cloud.google.com/spanner | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/neptune/developer-resources | druid.apache.org/docs/latest/design | kylin.apache.org/docs | cloud.google.com/spanner/docs | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Apache Software Foundation and contributors | Apache Software Foundation, originally contributed from eBay Inc | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2017 | 2012 | 2015 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 29.0.1, April 2024 | 3.1.0, July 2020 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source Apache license v2 | Open Source Apache Version 2.0 | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X Unix | Linux | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes schema-less columns are supported | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL for querying | ANSI SQL for queries (using Apache Calcite) | yes Query statements complying to ANSI 2011 | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | OpenCypher RDF 1.1 / SPARQL 1.1 TinkerPop Gremlin | JDBC RESTful HTTP/JSON API | JDBC ODBC RESTful HTTP API | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements. RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Go Java JavaScript PHP Python Ruby Scala | Clojure JavaScript PHP Python R Ruby Scala | Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding manual/auto, time-based | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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. | yes, via HDFS, S3 or other storage engines | Multi-source replication with 3 replicas for regional instances. | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | yes | yes using Google Cloud Dataflow | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in graphs | no | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | ACID Strict serializable isolation | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes with encyption-at-rest | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM) | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon Neptune | Apache Druid | Apache Kylin | Google Cloud Spanner | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 Monitoring PostgreSQL with Redgate Monitor 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 ... AWS announces Amazon Neptune I/O-Optimized Amazon Neptune Analytics is now available in the AWS Europe (London) Region Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ... provided by Google News 'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers Imply Data gives Apache Druid schema auto-discover capability Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ... provided by Google News Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance Introducing Kyligence Copilot: The AI Copilot for Data to Excel Your KPIs Overhauling Apache Kylin for the cloud eBay's Kylin Becomes a Top-Level Apache Open Source Project How Kyligence Cloud uses Amazon EMR Serverless to simplify OLAP | Amazon Web Services provided by Google News Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google makes its Cloud Spanner database service faster and more cost-efficient Google Spanner: When Do You Need to Move to It? Google Cloud Spanner Is Now Half the Cost of Amazon DynamoDB provided by Google News AGEDB Technology Launches PGTS - PostgreSQL Tech-Support Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need PostgreSQL Security Flaws Let Attackers Execute Code Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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