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DBMS > Apache Pinot vs. Drizzle vs. LeanXcale vs. Splice Machine

System Properties Comparison Apache Pinot vs. Drizzle vs. LeanXcale vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonDrizzle  Xexclude from comparisonLeanXcale  Xexclude from comparisonSplice Machine  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitepinot.apache.orgwww.leanxcale.comsplicemachine.com
Technical documentationdocs.pinot.apache.orgsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsDrizzle project, originally started by Brian AkerLeanXcaleSplice Machine
Initial release2015200820152014
Current release1.0.0, September 20237.2.4, September 20123.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll OS with a Java JDK11 or higherFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
Secondary indexesyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsyes infothrough Apache Derbyyes
APIs and other access methodsJDBCJDBCJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
C
C++
Java
PHP
C
Java
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersno infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PinotDrizzleLeanXcaleSplice Machine
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