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DBMS > Apache IoTDB vs. Databricks vs. Ehcache vs. Sphinx vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. Databricks vs. Ehcache vs. Sphinx vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkThe 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.A widely adopted Java cache with tiered storage optionsOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSDocument store
Relational DBMS
Key-value storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.79
Rank#66  Overall
#8  Key-value stores
Score5.97
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.databricks.comwww.ehcache.orgsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databricks.comwww.ehcache.org/­documentationsphinxsearch.com/­docs
DeveloperApache Software FoundationDatabricksTerracotta Inc, owned by Software AGSphinx Technologies Inc.Teradata
Initial release20182013200920012005
Current release1.1.0, April 20233.10.0, March 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languagewith Databricks SQLnoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
JCacheProprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Python
R
Scala
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnonoR packages
Triggersyesyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoby using Terracotta ServerSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes infoby using Terracotta Servernoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes infosupports JTA and can work as an XA resourcenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing a tiered cache-storage approachyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlyesnonofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBDatabricksEhcacheSphinxTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBDatabricksEhcacheSphinxTeradata Aster
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