DBMS > AnzoGraph DB vs. Apache Druid vs. HarperDB vs. HugeGraph vs. PostgreSQL
System Properties Comparison AnzoGraph DB vs. Apache Druid vs. HarperDB vs. HugeGraph vs. PostgreSQL
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| Name | AnzoGraph DB Xexclude from comparison | Apache Druid Xexclude from comparison | HarperDB Xexclude from comparison | HugeGraph 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 | Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture. | A fast-speed and highly-scalable Graph DBMS | 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 | Document store | Graph 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 AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | cambridgesemantics.com/anzograph | druid.apache.org | www.harperdb.io | github.com/hugegraph hugegraph.apache.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.cambridgesemantics.com/anzograph/userdoc/home.htm | druid.apache.org/docs/latest/design | docs.harperdb.io/docs | hugegraph.apache.org/docs | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Cambridge Semantics | Apache Software Foundation and contributors | HarperDB | Baidu | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2018 | 2012 | 2017 | 2018 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.3, January 2021 | 29.0.1, April 2024 | 3.1, August 2021 | 0.9 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial free trial version available | Open Source Apache license v2 | commercial free community edition available | Open Source Apache Version 2.0 | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Java | Node.js | Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux | Linux OS X Unix | Linux OS X | Linux macOS Unix | 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 | dynamic schema | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes JSON data types | 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 also supports composite index and range index | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SPARQL and SPARQL* as primary query language. Cypher preview. | SQL for querying | SQL-like data manipulation statements | no | 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 | JDBC ODBC React Hooks RESTful HTTP/JSON API WebSocket | Java API RESTful HTTP API TinkerPop Gremlin | 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 | .Net C C# C++ ColdFusion D Dart Delphi Erlang Go Haskell Java JavaScript (Node.js) Lisp MatLab Objective C Perl PHP PowerShell Prolog Python R Ruby Rust Scala Swift | Groovy Java Python | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | user defined functions and aggregates | no | Custom Functions since release 3.1 | asynchronous Gremlin script jobs | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Automatic sharding | Sharding manual/auto, time-based | A table resides as a whole on one (or more) nodes in a cluster | yes depending on used storage backend, e.g. Cassandra and HBase | 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 | yes the nodes on which a table resides can be defined | yes depending on used storage backend, e.g. Cassandra and HBase | 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 | no | via hugegraph-spark | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency in MPP-Cluster | Immediate Consistency | Immediate Consistency | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no not needed in graphs | no | no | yes edges in graph | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | Atomic execution of specific operations | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes, using LMDB | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes | yes | 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 and roles | Users, roles and permissions | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| AnzoGraph DB | Apache Druid | HarperDB | HugeGraph | 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 AnzoGraph review: A graph database for deep analytics Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access Back to the future: Does graph database success hang on query language? 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 Apache Druid Takes Its Place In The Pantheon Of Databases How to connect DataGrip to Apache Druid | by Zisis Flokas provided by Google News Serent Capital invests in software firm HarperDB HarperDB Attracts Significant Growth Investment from Serent Capital HarperDB Receives Growth Investment from Serent Capital Startups of the Year 2023: Meet HarperDB - A Database and Application Development Platform Jaxon Repp on HarperDB Distributed Database Platform provided by Google News POC exploit code published for critical Apache HugeGraph bug Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code PoC Exploit Released for High Severity Apache HugeGraph RCE flaw AI, Lockbit, Veeam, Club Penguin, Kali, Commando Cat, HugeGraph, Aaran Leyland… – SWN #391 Microsoft's Recall criticized for security shortcomings. Cyberespionage in Ukraine. provided by Google News Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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