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DBMS > Apache Impala vs. Cachelot.io vs. EJDB vs. GridDB vs. TimescaleDB

System Properties Comparison Apache Impala vs. Cachelot.io vs. EJDB vs. GridDB vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCachelot.io  Xexclude from comparisonEJDB  Xexclude from comparisonGridDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopIn-memory caching systemEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Scalable in-memory time series database optimized for IoT and Big DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeDocument storeTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.04
Rank#388  Overall
#62  Key-value stores
Score0.31
Rank#296  Overall
#44  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteimpala.apache.orgcachelot.iogithub.com/­Softmotions/­ejdbgriddb.netwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.griddb.netdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSoftmotionsToshiba CorporationTimescale
Initial release20132015201220132017
Current release4.1.0, June 20225.1, August 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoSimplified BSD LicenseOpen Source infoGPLv2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++CC++C
Server operating systemsLinuxFreeBSD
Linux
OS X
server-lessLinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes infostring, integer, double, bool, date, object_idyes infonumerical, string, blob, geometry, boolean, timestampnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL92, SQL-like TQL (Toshiba Query Language)yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Memcached protocolin-process shared libraryJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornonenoneSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono infotypically not needed, however similar functionality with collection joins possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnonoAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaCachelot.ioEJDBGridDBTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaCachelot.ioEJDBGridDBTimescaleDB
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