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DBMS > Drizzle vs. Neo4j vs. Sqrrl vs. YugabyteDB

System Properties Comparison Drizzle vs. Neo4j vs. Sqrrl vs. YugabyteDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonNeo4j  Xexclude from comparisonSqrrl  Xexclude from comparisonYugabyteDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Open source graph databaseAdaptable, secure NoSQL built on Apache AccumuloHigh-performance distributed SQL database for global, internet-scale applications. Wire compatible with PostgreSQL.
Primary database modelRelational DBMSGraph DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score51.66
Rank#22  Overall
#1  Graph DBMS
Score0.78
Rank#171  Overall
#83  Relational DBMS
Websiteneo4j.comsqrrl.comwww.yugabyte.com
Technical documentationneo4j.com/­docsdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperDrizzle project, originally started by Brian AkerNeo4j, Inc.Amazon infooriginally Sqrrl Data, Inc.YugaByte Inc.
Initial release2008200720122017
Current release7.2.4, September 20124.0.0, January 20202.0.10, January 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoGPL version3, commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, ScalaJavaC and C++
Server operating systemsFreeBSD
Linux
OS X
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
LinuxLinux
OS X
Data schemeyesschema-free and schema-optionalschema-freedepending on used data model
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Luceneyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes, PostgreSQL compatible
APIs and other access methodsJDBCBolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
Supported programming languagesC
C++
Java
PHP
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoUser defined Procedures and Functionsnoyes infosql, plpgsql, C
Triggersno infohooks for callbacks inside the server can be used.yes infovia event handlernoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replication
Master-slave replication
Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlyselectable replication factor infomaking use of HadoopBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityyesyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic updates per row, document, or graph entityDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)yes
More information provided by the system vendor
DrizzleNeo4jSqrrlYugabyteDB
Specific characteristicsNeo4j is a native graph database platform that is built to store, query, analyze...
» more
Competitive advantagesNeo4j database is the only transactional database that combines everything you need...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 300 commercial customers and over 750 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than a 15 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
News

This Week in Neo4j – Managing Multiple Databases, When and how to implement Sharding, Building Possibility Spaces with Neo4j and ReactJS, Australian Open Graph
25 January 2020

This Week in Neo4j – Discovering the Soul of a Product, UK Singles Chart Graph, Building Real-Time UIs with Kafka and Vue.js
18 January 2020

Creating Aha Moments for Developers: The 5-Minute Interview with Jennifer Reif, Developer Relations Engineer at Neo4j
17 January 2020

Graphs to Fight Diabetes
15 January 2020

This Week in Neo4j – Analyzing .NET Dependencies, Coloring a Sudoku Graph, Christmas Messages Graph, Making Graph Algorithms ‘Clique’
11 January 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DrizzleNeo4jSqrrlYugabyteDB
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