DBMS > Elasticsearch vs. Google Cloud Datastore vs. Sqrrl

System Properties Comparison Elasticsearch vs. Google Cloud Datastore vs. Sqrrl

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Editorial information provided by DB-Engines
Name	Elasticsearch  Xexclude from comparison	Google Cloud Datastore  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	A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric	Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform	Adaptable, secure NoSQL built on Apache Accumulo
Primary database model	Search engine	Document store	Document store Graph DBMS Key-value store Wide column store
Secondary database models	Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 154.33 Rank #8   Overall #1   Search engines	Score 5.75 Rank #71   Overall #12   Document stores
Website	www.elastic.co/­elasticsearch	cloud.google.com/­datastore	sqrrl.com
Technical documentation	www.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html	cloud.google.com/­datastore/­docs
Developer	Elastic	Google	Amazon originally Sqrrl Data, Inc.
Initial release	2010	2008	2012
Current release	7.8.0, June 2020
License Commercial or Open Source	Open Source Elastic License	commercial	commercial
Cloud-based only Only available as a cloud service	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java		Java
Server operating systems	All OS with a Java VM	hosted	Linux
Data scheme	schema-free Flexible type definitions. Once a type is defined, it is persistent	schema-free	schema-free
Typing predefined data types such as float or date	yes	yes, details here	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
Secondary indexes	yes All search fields are automatically indexed	yes	yes
SQL Support of SQL	SQL-like query language	SQL-like query language (GQL)	no
APIs and other access methods	Java API RESTful HTTP/JSON API	gRPC (using protocol buffers) API RESTful HTTP/JSON API	Accumulo Shell Java API JDBC ODBC RESTful HTTP API Thrift
Supported programming languages	.Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby	.Net Go Java JavaScript (Node.js) PHP Python Ruby	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	using Google App Engine	no
Triggers	yes by using the 'percolation' feature	Callbacks using the Google Apps Engine	no
Partitioning methods Methods for storing different data on different nodes	Sharding	Sharding	Sharding making use of Hadoop
Replication methods Methods for redundantly storing data on multiple nodes	yes	Multi-source replication using Paxos	selectable replication factor making use of Hadoop
MapReduce Offers an API for user-defined Map/Reduce methods	ES-Hadoop Connector	yes using Google Cloud Dataflow	yes
Consistency concepts Methods to ensure consistency in a distributed system	Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all	Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.	Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys Referential integrity	no	yes via ReferenceProperties or Ancestor paths	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	ACID Serializable Isolation within Transactions, Read Committed outside of Transactions	Atomic updates per row, document, or graph entity
Concurrency Support for concurrent manipulation of data	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	Memcached and Redis integration	no
User concepts Access control		Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
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More resources
	Elasticsearch	Google Cloud Datastore	Sqrrl
DB-Engines blog posts	PostgreSQL is the DBMS of the Year 2017 2 January 2018, Paul Andlinger, Matthias Gelbmann Elasticsearch moved into the top 10 most popular database management systems 3 July 2017, Matthias Gelbmann MySQL, PostgreSQL and Redis are the winners of the March ranking 2 March 2016, Paul Andlinger show all