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

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

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache IoTDB  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 StorageAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMySQL 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
Time Series DBMSRelational 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
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitedrill.apache.orgiotdb.apache.orggeode.apache.orgwww.kinetica.com
Technical documentationdrill.apache.org/­docsiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgeode.apache.org/­docsdocs.kinetica.com
DeveloperApache Software FoundationApache Software FoundationDrizzle 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 release20122018200820022012
Current release1.20.3, January 20231.1.0, April 20237.2.4, September 20121.1, February 20177.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC, C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languageyes infowith proprietary extensionsSQL-like query language (OQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native API
JDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC++C
C#
C++
Go
Java
Python
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 functionsyesnouser defined functionsuser defined functions
Triggersnoyesno 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 nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDyes, 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 sourceyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlDepending on the underlying data sourceyesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableAccess rights for users and roles on table level

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More resources
Apache DrillApache IoTDBDrizzleGeodeKinetica
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