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DBMS > Apache Impala vs. CrateDB vs. Tibero vs. ToroDB

System Properties Comparison Apache Impala vs. CrateDB vs. Tibero vs. ToroDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCrateDB  Xexclude from comparisonTibero  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopDistributed Database based on LuceneA secure RDBMS, designed for easy portability from OracleA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score1.59
Rank#148  Overall
#68  Relational DBMS
Websiteimpala.apache.orgcratedb.comus.tmaxsoft.com/­products/­tiberogithub.com/­torodb/­server
Technical documentationimpala.apache.org/­impala-docs.htmlcratedb.com/­docstechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCrateTmaxSoft8Kdata
Initial release2013201320032016
Current release4.1.0, June 20226, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2Open SourcecommercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageC++JavaC and AssemblerJava
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
HP-UX
Linux
Solaris
Windows
All OS with a Java 7 VM
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infostring, integer, double, boolean, date, object_id
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.nonoyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesAll languages supporting JDBC/ODBC.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions (Javascript)Persistent Stored Procedure (PSM)
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoby range, hash, list or compositeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono infoplanned for next version
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsfine grained access rights according to SQL-standard (SQL 92, SQL 99)Access rights for users and roles
More information provided by the system vendor
Apache ImpalaCrateDBTiberoToroDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Apache ImpalaCrateDBTiberoToroDB
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