DBMS > Heroic vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. Riak TS

System Properties Comparison Heroic vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. Riak TS

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Editorial information provided by DB-Engines
Name	Heroic  Xexclude from comparison	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse  Xexclude from comparison	Postgres-XL  Xexclude from comparison	Riak TS  Xexclude from comparison
Description	Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch	Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features	Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database model	Time Series DBMS	Relational DBMS	Relational DBMS	Time Series DBMS
Secondary database models			Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.46 Rank #265   Overall #22   Time Series DBMS	Score 19.93 Rank #31   Overall #19   Relational DBMS	Score 0.53 Rank #254   Overall #117   Relational DBMS	Score 0.28 Rank #307   Overall #27   Time Series DBMS
Website	github.com/­spotify/­heroic	azure.microsoft.com/­services/­synapse-analytics	www.postgres-xl.org
Technical documentation	spotify.github.io/­heroic	docs.microsoft.com/­azure/­synapse-analytics	www.postgres-xl.org/­documentation	www.tiot.jp/­riak-docs/­riak/­ts/­latest
Developer	Spotify	Microsoft		Open Source, formerly Basho Technologies
Initial release	2014	2016	2014 since 2012, originally named StormDB	2015
Current release			10 R1, October 2018	3.0.0, September 2022
License Commercial or Open Source	Open Source Apache 2.0	commercial	Open Source Mozilla public license	Open Source
Cloud-based only Only available as a cloud service	no	yes	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C++	C	Erlang
Server operating systems		hosted	Linux macOS	Linux OS X
Data scheme	schema-free	yes	yes	schema-free
Typing predefined data types such as float or date	yes	yes	yes	no
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 XML type, but no XML query functionality	no
Secondary indexes	yes via Elasticsearch	yes	yes	restricted
SQL Support of SQL	no	yes	yes distributed, parallel query execution	yes, limited
APIs and other access methods	HQL (Heroic Query Language, a JSON-based language) HTTP API	ADO.NET JDBC ODBC	ADO.NET JDBC native C library ODBC streaming API for large objects	HTTP API Native Erlang Interface
Supported programming languages		C# Java PHP	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl	C unofficial client library C# C++ unofficial client library Clojure unofficial client library Dart unofficial client library Erlang Go unofficial client library Groovy unofficial client library Haskell unofficial client library Java JavaScript unofficial client library Lisp unofficial client library Perl unofficial client library PHP Python Ruby Scala unofficial client library Smalltalk unofficial client library
Server-side scripts Stored procedures	no	Transact SQL	user defined functions	Erlang
Triggers	no	no	yes	yes pre-commit hooks and post-commit hooks
Partitioning methods Methods for storing different data on different nodes	Sharding	Sharding, horizontal partitioning	horizontal partitioning	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	yes	yes		selectable replication factor
MapReduce Offers an API for user-defined Map/Reduce methods	no	no	no	yes
Consistency concepts Methods to ensure consistency in a distributed system	Eventual Consistency Immediate Consistency	Immediate Consistency	Immediate Consistency	Eventual Consistency
Foreign keys Referential integrity	no	no docs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints	yes	no links between datasets can be stored
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	ACID	ACID MVCC	no
Concurrency Support for concurrent manipulation of data	yes	yes	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		no
User concepts Access control		yes	fine grained access rights according to SQL-standard	no
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More resources
	Heroic	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse	Postgres-XL	Riak TS
Recent citations in the news	Review: Google Bigtable scales with ease 7 September 2016, InfoWorld provided by Google News	General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA | Azure updates 8 April 2024, azure.microsoft.com Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates 22 March 2024, azure.microsoft.com Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform 24 September 2023, DataScientest Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services 18 October 2023, AWS Blog Azure Synapse vs. Databricks: Data Platform Comparison 2024 26 March 2024, eWeek provided by Google News		New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications 7 June 2015, insideBIGDATA provided by Google News

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