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DBMS > Databricks vs. Drizzle vs. EsgynDB vs. JanusGraph vs. Microsoft Azure Synapse Analytics

System Properties Comparison Databricks vs. Drizzle vs. EsgynDB vs. JanusGraph vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websitewww.databricks.comwww.esgyn.cnjanusgraph.orgazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.databricks.comdocs.janusgraph.orgdocs.microsoft.com/­azure/­synapse-analytics
DeveloperDatabricksDrizzle project, originally started by Brian AkerEsgynLinux Foundation; originally developed as Titan by AureliusMicrosoft
Initial release20132008201520172016
Current release7.2.4, September 20120.6.3, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaJavaC++
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinux
OS X
Unix
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesyes
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.yesnonono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsyesnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCADO.NET
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.NetClojure
Java
Python
C#
Java
PHP
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava Stored ProceduresyesTransact SQL
Triggersno infohooks for callbacks inside the server can be used.noyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesyes infoRelationships in graphsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Serveryes
More information provided by the system vendor
DatabricksDrizzleEsgynDBJanusGraph infosuccessor of TitanMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDrizzleEsgynDBJanusGraph infosuccessor of TitanMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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