DBMS > DuckDB vs. Google Cloud Bigtable vs. GraphDB vs. Kdb vs. PostgreSQL
System Properties Comparison DuckDB vs. Google Cloud Bigtable vs. GraphDB vs. Kdb vs. PostgreSQL
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Name | DuckDB Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | GraphDB former name: OWLIM Xexclude from comparison | Kdb Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | An embeddable, in-process, column-oriented SQL OLAP RDBMS | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL. | High performance Time Series DBMS | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Key-value store Wide column store | Graph DBMS RDF store | Time Series DBMS Vector 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 | Relational DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | duckdb.org | cloud.google.com/bigtable | www.ontotext.com | kx.com | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | duckdb.org/docs | cloud.google.com/bigtable/docs | graphdb.ontotext.com/documentation | code.kx.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Social network pages | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Ontotext | Kx Systems, a division of First Derivatives plc | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 2015 | 2000 | 2000 kdb was released 2000, kdb+ in 2003 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 1.0.0, June 2024 | 10.4, October 2023 | 3.6, May 2018 | 16.4, August 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source MIT License | commercial | commercial Some plugins of GraphDB Workbench are open sourced | commercial free 32-bit version | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ | Java | q | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | server-less | hosted | All OS with a Java VM Linux OS X Windows | Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | schema-free and OWL/RDFS-schema support; RDF shapes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | 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 | no | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes | yes table attribute 'grouped' | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | no | stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC | SQL-like query language (q) | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Arrow Database Connectivity (ADBC) CLI Client JDBC ODBC | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | GeoSPARQL GraphQL GraphQL Federation Java API JDBC RDF4J API RDFS RIO Sail API Sesame REST HTTP Protocol SPARQL 1.1 | HTTP API JDBC Jupyter Kafka ODBC WebSocket | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# 3rd party driver C++ Crystal 3rd party driver Go 3rd party driver Java Lisp 3rd party driver Python R Ruby 3rd party driver Rust Swift Zig 3rd party driver | C# C++ Go Java JavaScript (Node.js) Python | .Net C# Clojure Java JavaScript (Node.js) PHP Python Ruby Scala | C C# C++ Go J Java JavaScript Lua MatLab Perl PHP Python R Scala | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | well-defined plugin interfaces; JavaScript server-side extensibility | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | no | yes with views | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding | none | horizontal partitioning | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | none | Internal replication in Colossus, and regional replication between two clusters in different zones | Multi-source replication | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no similar paradigm used for internal processing | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request) | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes Constraint checking | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | ACID | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes, multi-version concurrency control (MVCC) | 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 | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | no | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on. | rights management via user accounts | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DuckDB | Google Cloud Bigtable | GraphDB former name: OWLIM | Kdb | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Ontotext GraphDB is a semantic database engine that allows organizations to build... » more | Integrated columnar database & programming system for streaming, real time and historical... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment... » more | provides seamless scalability; runs on industry standard server platforms; is top-ranked... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Metadata enrichment and management, linked data publishing, semantic inferencing... » more | tick database streaming sensor data massive intelligence applications oil and gas... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | GraphDB provides a platform for building next-generation AI and Knowledge Graph... » more | Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GraphDB is the most utilized semantic triplestore for mission-critical enterprise... » more | kdb+ performance and reliability proven by our customers in critical infrastructure... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition... » more | upon request » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery Using Entity Linking to Turn Your Graph into a Knowledge Graph Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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DuckDB | Google Cloud Bigtable | GraphDB former name: OWLIM | Kdb | 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 PASS Data Community Summit LLM-Assisted Translation From Postgres to SQLite and DuckDB My First Billion (of Rows) in DuckDB Reading PCAP Files (Directly) With DuckDB TigerEye Open Sources DuckDB.dart DuckDB: The tiny but powerful analytics database provided by Google News Google Cloud adds graph processing to Spanner, SQL support to Bigtable Google introduces Bigtable SQL access and Spanner's new AI-ready features Google's AI-First Strategy Brings Vector Support To Cloud Databases Google Cloud Adds GenAI, Core Enhancements Across Data Platform Google says it’ll stop charging fees to transfer data out of Google Cloud provided by Google News Ontotext’s GraphDB Solution Now Available on the Microsoft Azure Marketplace Ontotext's GraphDB Solution Now Available in the AWS Marketplace Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released Ontotext and Ontopic Join Forces to Revolutionize Data Virtualization Knowledge graphs change the nature of business intelligence provided by Google News Turbocharging the Engine: KX Unleashes AI-First Transformation with kdb+ Introducing Amazon FinSpace with Managed kdb Insights, a fully managed analytics engine, commonly used by capital markets customers for analysis of real-time and historical time series data McLaren Applied and KX partner to enhance ATLAS software analytics capabilities Stifel Turns to KX to Strengthen Market Intelligence and Trade Execution Impact KX Brings the Power and Performance of kdb+ to Python Developers with PyKX provided by Google News YugabyteDB 2.19 gets new PostgreSQL-compatibility features YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale Intel Demonstrates Up To 48% Improvement For AVX-512 Optimized PostgreSQL PostgreSQL in line for DuckDB-shaped boost in analytics arena PostgreSQL databases under attack provided by Google News |
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