DBMS > Apache Druid vs. Google Cloud Spanner vs. KeyDB vs. MarkLogic vs. PostgreSQL
System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. KeyDB vs. MarkLogic vs. PostgreSQL
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| Name | Apache Druid Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | KeyDB Xexclude from comparison | MarkLogic Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | 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. | An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols | Operational and transactional Enterprise NoSQL database | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS Time Series DBMS | Relational DBMS | Key-value store | Document store Native XML DBMS RDF store as of version 7Search engine | 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 AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | druid.apache.org | cloud.google.com/spanner | github.com/Snapchat/KeyDB keydb.dev | www.marklogic.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | druid.apache.org/docs/latest/design | cloud.google.com/spanner/docs | docs.keydb.dev | docs.marklogic.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Apache Software Foundation and contributors | EQ Alpha Technology Ltd. | MarkLogic Corp. | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2012 | 2017 | 2019 | 2001 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 29.0.1, April 2024 | 11.0, December 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache license v2 | commercial | Open Source BSD-3 | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Java | C++ | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X Unix | hosted | Linux | Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes schema-less columns are supported | yes | schema-free | schema-free Schema can be enforced | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | 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 | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | yes by using the Redis Search module | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL for querying | yes Query statements complying to ANSI 2011 | no | yes SQL92 | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC RESTful HTTP/JSON API | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements.RESTful HTTP API | Proprietary protocol RESP - REdis Serialization Protoco | Java API Node.js Client API ODBC proprietary Optic API Proprietary Query API, introduced with version 9RESTful HTTP API SPARQL WebDAV XDBC XQuery XSLT | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | Clojure JavaScript PHP Python R Ruby Scala | Go Java JavaScript (Node.js) Python | C C# C++ Clojure Crystal D Dart Elixir Erlang Fancy Go Haskell Haxe Java JavaScript (Node.js) Lisp Lua MatLab Objective-C OCaml Pascal Perl PHP Prolog Pure Data Python R Rebol Ruby Rust Scala Scheme Smalltalk Swift Tcl Visual Basic | C C# C++ Java JavaScript (Node.js) Perl PHP Python Ruby | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | no | Lua | yes via XQuery or JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding manual/auto, time-based | Sharding | Sharding | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | yes, via HDFS, S3 or other storage engines | Multi-source replication with 3 replicas for regional instances. | Multi-source replication Source-replica replication | yes | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | yes using Google Cloud Dataflow | no | yes via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Eventual Consistency Strong eventual consistency with CRDTs | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID Strict serializable isolation | Optimistic locking, atomic execution of commands blocks and scripts | ACID can act as a resource manager in an XA/JTA transaction | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | yes, with Range Indexes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | 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) | simple password-based access control and ACL | Role-based access control at the document and subdocument levels | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Apache Druid | Google Cloud Spanner | KeyDB | MarkLogic | 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 Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards 'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers 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 Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google makes its Cloud Spanner database service faster and more cost-efficient Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google Spanner: When Do You Need to Move to It? More AI Added to Google Cloud's Databases provided by Google News Oh, snap! Snap snaps up database developer KeyDB Snap Acquires KeyDB for Open-Source Services Garnet–open-source faster cache-store speeds up applications, services Microsoft open-sources Garnet cache-store -- a Redis rival? Redis 6 arrives with multithreading for faster I/O provided by Google News Progress (PRGS) Set to Buy MarkLogic, Guides Upbeat Q4 Results MarkLogic “The NoSQL Database”. In the MarkLogic Query Console, you can… | by Abhay Srivastava | Apr, 2024 Database Platform to Simplify Complex Data | Progress Marklogic ABN AMRO Moves Progress-Powered Credit Store App to Azure Cloud; Achieves 40% Faster Data Processing, Lower ... AI can make logistics data as valuable as intelligence or operational data for mission success provided by Google News Let PostgreSQL Pick An Index For You Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need ServiceNow trades MariaDB for RaptorDB (PostgreSQL) General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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