DBMS > Blazegraph vs. Google Cloud Bigtable vs. MonetDB vs. PostgreSQL vs. Stardog
System Properties Comparison Blazegraph vs. Google Cloud Bigtable vs. MonetDB vs. PostgreSQL vs. Stardog
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Blazegraph Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | MonetDB Xexclude from comparison | PostgreSQL Xexclude from comparison | Stardog Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability. | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | A relational database management system that stores data in columns | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Key-value store Wide column store | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Graph DBMS RDF store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | blazegraph.com | cloud.google.com/bigtable | www.monetdb.org | www.postgresql.org | www.stardog.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | wiki.blazegraph.com | cloud.google.com/bigtable/docs | www.monetdb.org/Documentation | www.postgresql.org/docs | docs.stardog.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Blazegraph | MonetDB BV | PostgreSQL Global Development Group www.postgresql.org/developer | Stardog-Union | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2006 | 2015 | 2004 | 1989 1989: Postgres, 1996: PostgreSQL | 2010 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 2.1.5, March 2019 | Dec2023 (11.49), December 2023 | 16.3, May 2024 | 7.3.0, May 2020 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source extended commercial license available | commercial | Open Source Mozilla Public License 2.0 | Open Source BSD | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | FreeBSD Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux macOS Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | yes | yes | schema-free and OWL/RDFS-schema support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes RDF literal types | no | yes | 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 | yes specific XML-type available, but no XML query functionality. | no Import/export of XML data possible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes | yes | yes supports real-time indexing in full-text and geospatial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SPARQL is used as query language | no | yes SQL 2003 with some extensions | yes standard with numerous extensions | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Java API RESTful HTTP API SPARQL QUERY SPARQL UPDATE TinkerPop 3 | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | JDBC native C library MAPI library (MonetDB application programming interface) ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C++ Java JavaScript PHP Python Ruby | C# C++ Go Java JavaScript (Node.js) Python | C C++ Java JavaScript (Node.js) Perl PHP Python R Ruby | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | .Net Clojure Groovy Java JavaScript Python Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | yes, in SQL, C, R | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | user defined functions and aggregates, HTTP Server extensions in Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes | yes | yes via event handlers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding via remote tables | partitioning by range, list and (since PostgreSQL 11) by hash | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Internal replication in Colossus, and regional replication between two clusters in different zones | none Source-replica replication available in experimental status | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication in HA-Cluster | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency depending on configuration | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | Immediate Consistency in HA-Cluster | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in Graphs | no | yes | yes | yes relationships in graphs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | ACID | ACID | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Security and Authentication via Web Application Container (Tomcat, Jetty) | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | Access rights for users and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Blazegraph | Google Cloud Bigtable | MonetDB | PostgreSQL | Stardog | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Back to the future: Does graph database success hang on query language? Harnessing GPUs Delivers a Big Speedup for Graph Analytics This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines Representation Learning on RDF* and LPG Knowledge Graphs Faster with GPUs: 5 turbocharged databases provided by Google News | Google's AI-First Strategy Brings Vector Support To Cloud Databases Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable provided by Google News | In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ... MonetDB Secures Investment From (and Partners With) ServiceNow PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho Monet DB The Column-Store Pioneer - open source for you provided by Google News | PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News |
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