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DBMS > Apache Drill vs. Databricks vs. Drizzle vs. Geode vs. Kinetica

System Properties Comparison Apache Drill vs. Databricks vs. Drizzle vs. Geode vs. Kinetica

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonKinetica  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.
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageThe 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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Relational DBMS
Document store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitedrill.apache.orgwww.databricks.comgeode.apache.orgwww.kinetica.com
Technical documentationdrill.apache.org/­docsdocs.databricks.comgeode.apache.org/­docsdocs.kinetica.com
DeveloperApache Software FoundationDatabricksDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Kinetica
Initial release20122013200820022012
Current release1.20.3, January 20237.2.4, September 20121.1, February 20177.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC, C++
Server operating systemsLinux
OS X
Windows
hostedFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
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.noyesnono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantwith Databricks SQLyes infowith proprietary extensionsSQL-like query language (OQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++Python
R
Scala
C
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesnouser defined functionsuser defined functions
Triggersnono infohooks for callbacks inside the server can be used.yes infoCache Event Listenersyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlDepending on the underlying data sourcePluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableAccess rights for users and roles on table level
More information provided by the system vendor
Apache DrillDatabricksDrizzleGeodeKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DrillDatabricksDrizzleGeodeKinetica
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