DBMS > ArcadeDB vs. Atos Standard Common Repository vs. DolphinDB vs. Google Cloud Bigtable

System Properties Comparison ArcadeDB vs. Atos Standard Common Repository vs. DolphinDB vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
Name	ArcadeDB  Xexclude from comparison	Atos Standard Common Repository  Xexclude from comparison	DolphinDB  Xexclude from comparison	Google Cloud Bigtable  Xexclude from comparison
		This system has been discontinued and will be removed from the DB-Engines ranking.
Description	Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten	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.	Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database model	Document store Graph DBMS Key-value store Time Series DBMS in next version	Document store Key-value store	Time Series DBMS	Key-value store Wide column store
Secondary database models			Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.10 Rank #358   Overall #48   Document stores #38   Graph DBMS #52   Key-value stores #35   Time Series DBMS		Score 4.03 Rank #78   Overall #6   Time Series DBMS	Score 3.15 Rank #95   Overall #14   Key-value stores #8   Wide column stores
Website	arcadedb.com	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.dolphindb.com	cloud.google.com/­bigtable
Technical documentation	docs.arcadedb.com		docs.dolphindb.cn/­en/­help200/­index.html	cloud.google.com/­bigtable/­docs
Developer	Arcade Data	Atos Convergence Creators	DolphinDB, Inc	Google
Initial release	2021	2016	2018	2015
Current release	September 2021	1703	v2.00.4, January 2022
License Commercial or Open Source	Open Source Apache Version 2.0	commercial	commercial free community version available	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	Java	C++
Server operating systems	All OS with a Java VM	Linux	Linux Windows	hosted
Data scheme	schema-free	Schema and schema-less with LDAP views	yes	schema-free
Typing predefined data types such as float or date	yes	optional	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	yes	no	no
Secondary indexes	yes	yes	yes	no
SQL Support of SQL	SQL-like query language, no joins	no	SQL-like query language	no
APIs and other access methods	JDBC MongoDB API OpenCypher PostgreSQL wire protocol Redis API RESTful HTTP/JSON API TinkerPop Gremlin	LDAP	JDBC JSON over HTTP Kafka MQTT (Message Queue Telemetry Transport) ODBC OPC DA OPC UA RabbitMQ WebSocket	gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java)
Supported programming languages	Java	All languages with LDAP bindings	C# C++ Go Java JavaScript MatLab Python R Rust	C# C++ Go Java JavaScript (Node.js) Python
Server-side scripts Stored procedures		no	yes	no
Triggers		yes	no	no
Partitioning methods Methods for storing different data on different nodes		Sharding cell division	horizontal partitioning	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	Source-replica replication	yes	yes	Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce Offers an API for user-defined Map/Reduce methods	no		yes	yes
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys Referential integrity	yes relationship in graphs	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	Atomic execution of specific operations	yes	Atomic single-row operations
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.		yes	yes	no
User concepts Access control		LDAP bind authentication	Administrators, Users, Groups	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
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More resources
	ArcadeDB	Atos Standard Common Repository	DolphinDB	Google Cloud Bigtable
Recent citations in the news		Infographic: What makes a Mobile Operator's setup future proof? 10 February 2024, Atos provided by Google News		Google's AI-First Strategy Brings Vector Support To Cloud Databases 1 March 2024, Forbes Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs 31 January 2022, InfoQ.com Google scales up Cloud Bigtable NoSQL database 27 January 2022, TechTarget Review: Google Bigtable scales with ease 7 September 2016, InfoWorld Google Cloud makes it cheaper to run smaller workloads on Bigtable 7 April 2020, TechCrunch provided by Google News

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