DBMS > AllegroGraph vs. Apache Druid vs. BaseX vs. Datastax Enterprise vs. PostgreSQL
System Properties Comparison AllegroGraph vs. Apache Druid vs. BaseX vs. Datastax Enterprise vs. PostgreSQL
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Name | AllegroGraph Xexclude from comparison | Apache Druid Xexclude from comparison | BaseX Xexclude from comparison | Datastax Enterprise Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | High performance, persistent RDF store with additional support for Graph DBMS | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI. | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store with version 6.5 Graph DBMS RDF store Vector DBMS | Relational DBMS Time Series DBMS | Native XML DBMS | 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 Spatial DBMS Search engine Vector DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | allegrograph.com | druid.apache.org | basex.org | www.datastax.com/products/datastax-enterprise | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | franz.com/agraph/support/documentation/current/agraph-introduction.html | druid.apache.org/docs/latest/design | docs.basex.org | docs.datastax.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Franz Inc. | Apache Software Foundation and contributors | BaseX GmbH | DataStax | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2004 | 2012 | 2007 | 2011 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.0, December 2023 | 29.0.1, April 2024 | 10.7, August 2023 | 6.8, April 2020 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Limited community edition free | Open Source Apache license v2 | Open Source BSD license | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | Java | Java | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | Linux OS X Unix | Linux OS X Windows | Linux OS X | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes RDF schemas | yes schema-less columns are supported | schema-free | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | no XQuery supports 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 bulk load of XML files possible | no | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SPARQL is used as query language | SQL for querying | no | SQL-like DML and DDL statements (CQL); Spark SQL | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | RESTful HTTP API SPARQL | JDBC RESTful HTTP/JSON API | Java API RESTful HTTP API RESTXQ WebDAV XML:DB XQJ | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Clojure Java Lisp Perl Python Ruby Scala | Clojure JavaScript PHP Python R Ruby Scala | Actionscript C C# Haskell Java JavaScript Node.js Lisp Perl PHP Python Qt Rebol Ruby Scala Visual Basic | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes JavaScript or Common Lisp | no | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | yes via events | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | with Federation | Sharding manual/auto, time-based | none | Sharding no "single point of failure" | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication Source-replica replication | yes, via HDFS, S3 or other storage engines | none | configurable replication factor, datacenter aware, advanced replication for edge computing | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | multiple readers, single writer | no Atomicity and isolation are supported for single operations | 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 | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Users with fine-grained authorization concept, user roles and pluggable authentication | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Users with fine-grained authorization concept on 4 levels | Access rights for users can be defined per object | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
AllegroGraph | Apache Druid | BaseX | Datastax Enterprise | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph... » more | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and... » more | Supporting the following application requirements: Zero downtime - Built on Apache... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Annual subscription » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Can Neuro-Symbolic AI Solve AI’s Weaknesses? 100 Companies That Matter in KM – Franz Inc. Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar) What is Neuro-Symbolic AI? Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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AllegroGraph | Apache Druid | BaseX | Datastax Enterprise | 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 Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses? AI predictions for 2024 unveil exciting technological horizons Jans Aasman Articles and Insights Neuro-Symbolic AI: The Peak of Artificial Intelligence Fuse Graph Neural Networks with Semantic Reasoning to Produce Complimentary Predictions 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 XML Injection Attacks: What to Know About XPath, XQuery, XXE & More 9 Skills You Need to Become a Data Engineer provided by Google News DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech DataStax goes vector searching with Astra DB – Blocks and Files DataStax delivers HIPAA-enabled, PCI compliant vector database to fuel enterprise-wide generative AI applications DataStax taps ThirdAI to bring generative AI to its database offerings provided by Google News Handle tables without primary keys while creating Amazon Aurora PostgreSQL zero-ETL integrations with Amazon ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Breaking Boundaries: PostgreSQL 16 is now available on IBM Cloud pgEdge Distributed PostgreSQL Introduces Automatic DDL Replication and Snowflake Sequences for Postgres PostgreSQL or MySQL: What Should I Choose for My Full-Stack Project? provided by Google News |
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