DBMS > Apache Druid vs. Faircom EDGE vs. Google Cloud Spanner vs. PostgreSQL
System Properties Comparison Apache Druid vs. Faircom EDGE vs. Google Cloud Spanner vs. PostgreSQL
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Name | Apache Druid Xexclude from comparison | Faircom EDGE formerly c-treeEDGE Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | PostgreSQL Xexclude from comparison | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data | FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments | A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play. | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Time Series DBMS | Key-value store Relational DBMS | Relational 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 Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | druid.apache.org | www.faircom.com/products/faircom-edge | cloud.google.com/spanner | www.postgresql.org | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | druid.apache.org/docs/latest/design | docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html | cloud.google.com/spanner/docs | www.postgresql.org/docs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation and contributors | FairCom Corporation | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 1979 | 2017 | 1989 1989: Postgres, 1996: PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 29.0.1, April 2024 | V3, October 2020 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache license v2 | commercial Restricted, free version available | commercial | Open Source BSD | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | ANSI C, C++ | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Unix | Android Linux ARM, x86 Raspbian Windows | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes schema-less columns are supported | Flexible Schema (defined schema, partial schema, schema free) | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes, ANSI Standard SQL 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 | yes | no | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL for querying | yes ANSI SQL queries | yes Query statements complying to ANSI 2011 | yes standard with numerous extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC RESTful HTTP/JSON API | ADO.NET Direct SQL IoT Microservice layer JDBC MQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements. RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Clojure JavaScript PHP Python R Ruby Scala | C C# C++ Java JavaScript PHP Python VB.Net | Go Java JavaScript (Node.js) Python | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | yes .Net, JavaScript, C/C++ | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding manual/auto, time-based | File partitioning Customizable business rules for partitioning | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes, via HDFS, S3 or other storage engines | yes Synchronous and asynchronous realtime replication based on transaction logs | Multi-source replication with 3 replicas for regional instances. | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | yes using Google Cloud Dataflow | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency Tunable Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes when using SQL | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID Strict serializable isolation | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes across SQL and NoSQL | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system | Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL. | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | fine grained access rights according to SQL-standard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Apache Druid | Faircom EDGE formerly c-treeEDGE | Google Cloud Spanner | 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 '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 FairCom kicks off new era of database technology USA - English Winners of the 2021 IoT Evolution Product of the Year Awards Announced Trend-Setting Products in Data and Information Management for 2023 How To Collect, Store, and Query IoT Data With MQTT + SQL Trend-Setting Products in Data and Information Management for 2024 provided by Google News Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google makes its Cloud Spanner database service faster and more cost-efficient Google Spanner: When Do You Need to Move to It? Google Cloud Spanner competes directly with Amazon DynamoDB provided by Google News PostgreSQL Security Flaws Let Attackers Execute Code AGEDB Technology Launches PGTS - PostgreSQL Tech-Support – Company Announcement - FT.com First Principles: Optimizing PostgreSQL for the cloud Automatically Generate Types for Your PostgreSQL Database Your MySQL 5.7 and PostgreSQL 11 databases will be automatically enrolled into Amazon RDS Extended Support ... provided by Google News |
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