DBMS > Apache Druid vs. Geode vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. PostgreSQL
System Properties Comparison Apache Druid vs. Geode vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. PostgreSQL
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Name | Apache Druid Xexclude from comparison | Geode Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | Microsoft Azure Cosmos DB former name was Azure DocumentDB 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 | Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes | 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. | Globally distributed, horizontally scalable, multi-model database service | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Time Series DBMS | Key-value store | Relational DBMS | Document store Graph DBMS Key-value store Wide column store | 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 | Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | druid.apache.org | geode.apache.org | cloud.google.com/spanner | azure.microsoft.com/services/cosmos-db | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | druid.apache.org/docs/latest/design | geode.apache.org/docs | cloud.google.com/spanner/docs | learn.microsoft.com/azure/cosmos-db | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation and contributors | Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire. | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 2002 | 2017 | 2014 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 29.0.1, April 2024 | 1.1, February 2017 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache license v2 | Open Source Apache Version 2; commercial licenses available as Gemfire | commercial | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Unix | All OS with a Java VM the JDK (8 or later) is also required | hosted | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes schema-less columns are supported | schema-free | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes JSON types | 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 specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes | yes All properties auto-indexed by default | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL for querying | SQL-like query language (OQL) | yes Query statements complying to ANSI 2011 | SQL-like query language | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC RESTful HTTP/JSON API | Java Client API Memcached protocol 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 | DocumentDB API Graph API (Gremlin) MongoDB API RESTful HTTP API Table API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Clojure JavaScript PHP Python R Ruby Scala | .Net All JVM based languages C++ Groovy Java Scala | Go Java JavaScript (Node.js) Python | .Net C# Java JavaScript JavaScript (Node.js) MongoDB client drivers written for various programming languages Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | user defined functions | no | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes Cache Event Listeners | no | JavaScript | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding manual/auto, time-based | Sharding | Sharding | Sharding Implicit feature of the cloud service | 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 | Multi-source replication with 3 replicas for regional instances. | yes Implicit feature of the cloud service | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | yes using Google Cloud Dataflow | with Hadoop integration Integration with Hadoop/HDInsight on Azure* | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency | Immediate Consistency | Bounded Staleness Consistent Prefix Eventual Consistency Immediate Consistency Consistency level configurable on request level Session Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | yes, on a single node | ACID Strict serializable isolation | Multi-item ACID transactions with snapshot isolation within a partition | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Access rights per client and object definable | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Access rights can be defined down to the item level | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Druid | Geode | Google Cloud Spanner | Microsoft Azure Cosmos DB former name was Azure DocumentDB | 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 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 This is how much one of the most expensive gems costs at the Tucson gem show Apache Geode Spawns 'All Sorts of In-Memory Things' Victor I. Cazares Wants NYTW to Call for Ceasefire in Gaza 1. Introduction to Pivotal GemFire In-Memory Data Grid and Apache Geode - Scaling Data Services with Pivotal ... Where Does Apache Geode Fit in CQRS Architectures? 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 General Availability: Data API builder | Azure updates Start your AI journey with Microsoft Azure Cosmos DB—compete for $10K Public preview: Change partition key of a container in Azure Cosmos DB (NoSQL API) | Azure updates Microsoft Ships Data API Builder for Azure SQL Databases General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News Distributed PostgreSQL Buyers Guide Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... SolarWinds Unveils Enhanced Database Performance Analyzer with Advanced PostgreSQL Support ServiceNow trades MariaDB for RaptorDB (PostgreSQL) anynines Launches Quick & Easy PostgreSQL Management in Local Kubernetes Clusters with a9s CLI provided by Google News |
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