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DBMS > Apache Druid vs. ObjectBox vs. Splice Machine vs. Teradata

System Properties Comparison Apache Druid vs. ObjectBox vs. Splice Machine vs. Teradata

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonObjectBox  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataExtremely fast embedded database for small devices, IoT and MobileOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Object oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedruid.apache.orgobjectbox.iosplicemachine.comwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.objectbox.iosplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperApache Software Foundation and contributorsObjectBox LimitedSplice MachineTeradata
Initial release2012201720141984
Current release29.0.1, April 20243.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache License 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinux
OS X
Unix
Android
iOS
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
hosted
Linux
Data schemeyes infoschema-less columns are supportedyesyesyes
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.nonoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL for queryingnoyesyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Proprietary native APIJDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonoyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesonline/offline synchronization between client and serverMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidObjectBoxSplice MachineTeradata
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