DBMS > Google Cloud Bigtable vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. PostgreSQL vs. Sqrrl
System Properties Comparison Google Cloud Bigtable vs. Google Cloud Datastore vs. Microsoft Azure Cosmos DB vs. PostgreSQL vs. Sqrrl
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Google Cloud Bigtable Xexclude from comparison | Google Cloud Datastore Xexclude from comparison | Microsoft Azure Cosmos DB former name was Azure DocumentDB Xexclude from comparison | PostgreSQL Xexclude from comparison | Sqrrl Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform | Globally distributed, horizontally scalable, multi-model database service | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Adaptable, secure NoSQL built on Apache Accumulo | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Wide column store | Document store | 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. | Document store Graph DBMS Key-value store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cloud.google.com/bigtable | cloud.google.com/datastore | azure.microsoft.com/services/cosmos-db | www.postgresql.org | sqrrl.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cloud.google.com/bigtable/docs | cloud.google.com/datastore/docs | learn.microsoft.com/azure/cosmos-db | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | Amazon originally Sqrrl Data, Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2008 | 2014 | 1989 1989: Postgres, 1996: PostgreSQL | 2012 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | commercial | Open Source BSD | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | hosted | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | schema-free | yes | schema-free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | no | yes, details here | yes JSON 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 | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes All properties auto-indexed by default | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like query language (GQL) | SQL-like query language | yes standard with numerous extensions | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | gRPC (using protocol buffers) API RESTful HTTP/JSON 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 | Accumulo Shell Java API JDBC ODBC RESTful HTTP API Thrift | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Go Java JavaScript (Node.js) Python | .Net Go Java JavaScript (Node.js) PHP Python Ruby | .Net C# Java JavaScript JavaScript (Node.js) MongoDB client drivers written for various programming languages Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | Actionscript C using GLib C# C++ Cocoa Delphi Erlang Go Haskell Java JavaScript OCaml Perl PHP Python Ruby Smalltalk | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | using Google App Engine | JavaScript | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | Callbacks using the Google Apps Engine | JavaScript | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding Implicit feature of the cloud service | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding making use of Hadoop | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Internal replication in Colossus, and regional replication between two clusters in different zones | Multi-source replication using Paxos | yes Implicit feature of the cloud service | Source-replica replication other methods possible by using 3rd party extensions | selectable replication factor making use of Hadoop | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes using Google Cloud Dataflow | with Hadoop integration Integration with Hadoop/HDInsight on Azure* | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent. | Bounded Staleness Consistent Prefix Eventual Consistency Immediate Consistency Consistency level configurable on request level Session Consistency | Immediate Consistency | Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes via ReferenceProperties or Ancestor paths | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | Atomic single-row operations | ACID Serializable Isolation within Transactions, Read Committed outside of Transactions | Multi-item ACID transactions with snapshot isolation within a partition | ACID | Atomic updates per row, document, or graph entity | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | 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 | Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Google Cloud Bigtable | Google Cloud Datastore | Microsoft Azure Cosmos DB former name was Azure DocumentDB | PostgreSQL | Sqrrl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Google says it'll stop charging fees to transfer data out of Google Cloud Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease Google introduces Cloud Bigtable managed NoSQL database to process data at scale provided by Google News | Google Cloud Platform: Professional Data Engineer certification prep Google Cloud Stops Exit Fees Best cloud storage of 2024 Inside Google’s strategic move to eliminate customer cloud data transfer fees BigID Data Intelligence Platform Now Available on Google Cloud Marketplace provided by Google News | Public Preview: DiskANN vector indexing and search in Azure Cosmos DB NoSQL | Azure updates Start your AI journey with Microsoft Azure Cosmos DB—compete for $10K Public Preview: vCore-based Azure Cosmos DB for MongoDB cross-region disaster recovery (DR) | Azure updates Building Planet-Scale .NET Apps with Azure Cosmos DB Public preview: Change partition key of a container in Azure Cosmos DB (NoSQL API) | Azure updates 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 How to implement a better like, views, comment counters in PostgreSQL? provided by Google News | Splunk details Sqrrl 'screw-ups' that hampered threat hunting Amazon's cloud business acquires Sqrrl, a security start-up with NSA roots Millennials possess the advantage of time for wealth creation, says Yashoraj Tyagi of Sqrrl | Mint AWS beefs up threat detection with Sqrrl acquisition Amazon acquires cybersecurity startup Sqrrl provided by Google News |
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