DBMS > DolphinDB vs. etcd vs. Hawkular Metrics vs. LokiJS vs. Sqrrl

System Properties Comparison DolphinDB vs. etcd vs. Hawkular Metrics vs. LokiJS vs. Sqrrl

Editorial information provided by DB-Engines
Name	DolphinDB  Xexclude from comparison	etcd  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	LokiJS  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	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.	A distributed reliable key-value store	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	In-memory JavaScript DBMS	Adaptable, secure NoSQL built on Apache Accumulo
Primary database model	Time Series DBMS	Key-value store	Time Series DBMS	Document store	Document store Graph 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 1.63 Rank #140   Overall #9   Time Series DBMS	Score 10.43 Rank #47   Overall #5   Key-value stores	Score 0.00 Rank #355   Overall #31   Time Series DBMS	Score 0.53 Rank #233   Overall #36   Document stores
Website	www.dolphindb.com	etcd.io github.com/­etcd-io/­etcd	www.hawkular.org	github.com/­techfort/­LokiJS	sqrrl.com
Technical documentation	www.dolphindb.com/­help	etcd.io/­docs github.com/­etcd-io/­etcd/­tree/­master/­Documentation	www.hawkular.org/­hawkular-metrics/­docs/­user-guide	techfort.github.io/­LokiJS
Developer	DolphinDB, Inc		Community supported by Red Hat		Amazon originally Sqrrl Data, Inc.
Initial release	2018		2014	2014	2012
Current release	v2.00.4, January 2022	3.4, August 2019
License Commercial or Open Source	commercial free community version available	Open Source Apache Version 2.0	Open Source Apache 2.0	Open Source	commercial
Cloud-based only Only available as a cloud service	no	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	C++	Go	Java	JavaScript	Java
Server operating systems	Linux Windows	FreeBSD Linux Windows experimental	Linux OS X Windows	server-less, requires a JavaScript environment (browser, Node.js)	Linux
Data scheme	yes	schema-free	schema-free	schema-free	schema-free
Typing predefined data types such as float or date	yes	no	yes	no	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	no	no
Secondary indexes	yes	no	no	yes via views	yes
SQL Support of SQL	SQL-like query language	no	no	no	no
APIs and other access methods	JDBC JSON over HTTP Kafka MQTT (Message Queue Telemetry Transport) ODBC OPC DA OPC UA RabbitMQ WebSocket	gRPC JSON over HTTP	HTTP REST	JavaScript API	Accumulo Shell Java API JDBC ODBC RESTful HTTP API Thrift
Supported programming languages	C# C++ Go Java JavaScript MatLab Python R Rust	.Net C C++ Clojure Erlang Go Haskell Java JavaScript (Node.js) Perl PHP Python R Ruby Rust Scala Tcl	Go Java Python Ruby	JavaScript	Actionscript C using GLib C# C++ Cocoa Delphi Erlang Go Haskell Java JavaScript OCaml Perl PHP Python Ruby Smalltalk
Server-side scripts Stored procedures	yes	no	no	View functions in JavaScript	no
Triggers	no	yes, watching key changes	yes via Hawkular Alerting	yes	no
Partitioning methods Methods for storing different data on different nodes	horizontal partitioning		Sharding based on Cassandra	none	Sharding making use of Hadoop
Replication methods Methods for redundantly storing data on multiple nodes	yes	Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.	selectable replication factor based on Cassandra	none	selectable replication factor making use of Hadoop
MapReduce Offers an API for user-defined Map/Reduce methods	yes	no	no	yes	yes
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Immediate Consistency	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra	none	Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys Referential integrity	no	no	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	yes	no	no	no atomic operations within a single collection possible	Atomic updates per row, document, or graph entity
Concurrency Support for concurrent manipulation of data	yes	yes	yes		yes
Durability Support for making data persistent	yes	yes	yes	yes Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	no	yes
User concepts Access control	Administrators, Users, Groups	no	no	no	Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
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More resources
	DolphinDB	etcd	Hawkular Metrics	LokiJS	Sqrrl
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