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DBMS > Apache Impala vs. Databricks vs. LevelDB vs. TDengine

System Properties Comparison Apache Impala vs. Databricks vs. LevelDB vs. TDengine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe 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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesTime Series DBMS and big data platform
Primary database modelRelational DBMSDocument store
Relational DBMS
Key-value storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteimpala.apache.orgwww.databricks.comgithub.com/­google/­leveldbgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.tdengine.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksGoogleTDEngine, previously Taos Data
Initial release2013201320112019
Current release4.1.0, June 20221.23, February 20213.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSDOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
Linux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLnoStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnono
Triggersnonoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnoyes
More information provided by the system vendor
Apache ImpalaDatabricksLevelDBTDengine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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