DBMS > AnzoGraph DB vs. Apache Druid vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. PostgreSQL
System Properties Comparison AnzoGraph DB vs. Apache Druid vs. Google Cloud Spanner vs. Microsoft Azure Cosmos DB vs. PostgreSQL
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| Name | AnzoGraph DB Xexclude from comparison | Apache Druid 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 | Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization | 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. | 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 | Graph DBMS RDF store | Relational DBMS Time Series DBMS | 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 AgeSpatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | cambridgesemantics.com/anzograph | druid.apache.org | cloud.google.com/spanner | azure.microsoft.com/services/cosmos-db | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.cambridgesemantics.com/anzograph/userdoc/home.htm | druid.apache.org/docs/latest/design | cloud.google.com/spanner/docs | learn.microsoft.com/azure/cosmos-db | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Cambridge Semantics | Apache Software Foundation and contributors | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2018 | 2012 | 2017 | 2014 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.3, January 2021 | 29.0.1, April 2024 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free trial version available | Open Source Apache license v2 | 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 | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux | Linux OS X Unix | hosted | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | Schema-free and OWL/RDFS-schema support | yes schema-less columns are supported | yes | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | 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 | no | yes | yes | yes All properties auto-indexed by default | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SPARQL and SPARQL* as primary query language. Cypher preview. | SQL for querying | yes Query statements complying to ANSI 2011 | SQL-like query language | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Apache Mule gRPC JDBC Kafka OData access for BI tools OpenCypher RESTful HTTP API SPARQL | 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 | 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 | C++ Java Python | Clojure JavaScript PHP Python R Ruby 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 JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | user defined functions and aggregates | no | no | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | no | no | JavaScript | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Automatic sharding | Sharding manual/auto, time-based | 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 | Multi-source replication in MPP-Cluster | yes, via HDFS, S3 or other storage engines | 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 | Kerberos/HDFS data loading | 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 in MPP-Cluster | Immediate Consistency | Immediate Consistency | Bounded Staleness Consistent Prefix Eventual Consistency Immediate Consistency Consistency level configurable on request levelSession Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no not needed in graphs | 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 | ACID | no | 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. | yes | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users and roles | 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) | Access rights can be defined down to the item level | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| AnzoGraph DB | Apache Druid | 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 AnzoGraph review: A graph database for deep analytics Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury Back to the future: Does graph database success hang on query language? Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable? provided by Google News 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 Public Preview: DiskANN vector indexing and search in Azure Cosmos DB NoSQL | Azure updates Public Preview: vCore-based Azure Cosmos DB for MongoDB cross-region disaster recovery (DR) | Azure updates Microsoft Build 2024: Cosmos DB for NoSQL gets vector search Start your AI journey with Microsoft Azure Cosmos DB—compete for $10K At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements provided by Google News Deep PostgreSQL Thoughts: Valuing Currency At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Nutanix partners with EDB to fit database service for AI – Blocks and Files How to Import CSV Data Into PostgreSQL Using Spring Boot Batch Nutanix and EDB enhance PostgreSQL for enterprise apps provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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