DBMS > Atos Standard Common Repository vs. DolphinDB vs. Heroic vs. PlanetScale

System Properties Comparison Atos Standard Common Repository vs. DolphinDB vs. Heroic vs. PlanetScale

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	DolphinDB  Xexclude from comparison	Heroic  Xexclude from comparison	PlanetScale  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.
Description	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.	Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch	Scalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database model	Document store Key-value store	Time Series DBMS	Time Series DBMS	Relational DBMS
Secondary database models		Relational DBMS		Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 4.03 Rank #78   Overall #6   Time Series DBMS	Score 0.46 Rank #265   Overall #22   Time Series DBMS	Score 1.49 Rank #155   Overall #72   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.dolphindb.com	github.com/­spotify/­heroic	planetscale.com
Technical documentation		docs.dolphindb.cn/­en/­help200/­index.html	spotify.github.io/­heroic	planetscale.com/­docs
Developer	Atos Convergence Creators	DolphinDB, Inc	Spotify	PlanetScale
Initial release	2016	2018	2014	2020
Current release	1703	v2.00.4, January 2022
License Commercial or Open Source	commercial	commercial free community version available	Open Source Apache 2.0	commercial
Cloud-based only Only available as a cloud service	no	no	no	yes
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C++	Java	Go
Server operating systems	Linux	Linux Windows		Docker Linux macOS
Data scheme	Schema and schema-less with LDAP views	yes	schema-free	yes
Typing predefined data types such as float or date	optional	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.	yes	no	no
Secondary indexes	yes	yes	yes via Elasticsearch	yes
SQL Support of SQL	no	SQL-like query language	no	yes with proprietary extensions
APIs and other access methods	LDAP	JDBC JSON over HTTP Kafka MQTT (Message Queue Telemetry Transport) ODBC OPC DA OPC UA RabbitMQ WebSocket	HQL (Heroic Query Language, a JSON-based language) HTTP API	ADO.NET JDBC MySQL protocol ODBC
Supported programming languages	All languages with LDAP bindings	C# C++ Go Java JavaScript MatLab Python R Rust		Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl
Server-side scripts Stored procedures	no	yes	no	yes proprietary syntax
Triggers	yes	no	no	yes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	horizontal partitioning	Sharding	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	yes	yes	yes	Multi-source replication Source-replica replication
MapReduce Offers an API for user-defined Map/Reduce methods		yes	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Eventual Consistency Immediate Consistency	Eventual Consistency across shards Immediate Consistency within a shard
Foreign keys Referential integrity	no	no	no	yes not for MyISAM storage engine
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	yes	no	ACID at shard level
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes table locks or row locks depending on storage engine
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.	yes	yes	no	yes
User concepts Access control	LDAP bind authentication	Administrators, Users, Groups		Users with fine-grained authorization concept no user groups or roles
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More resources
	Atos Standard Common Repository	DolphinDB	Heroic	PlanetScale
Recent citations in the news			Review: Google Bigtable scales with ease 7 September 2016, InfoWorld provided by Google News	PlanetScale ends free tier bid, sheds staff in profitability bid 11 March 2024, The Register PlanetScale Ranked Number 188 Fastest-Growing Company in North America on the 2023 Deloitte Technology Fast ... 8 November 2023, businesswire.com PlanetScale forks MySQL to add vector support 3 October 2023, TechCrunch PlanetScale Named to Fortune 2023 Best Small Workplaces 31 August 2023, businesswire.com How to Migrate to PlanetScale's Serverless Database 14 October 2021, The New Stack provided by Google News

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