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DBMS > Apache Impala vs. Google Cloud Bigtable vs. RRDtool vs. Tibero

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. RRDtool vs. Tibero

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRRDtool  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.A secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score1.78
Rank#140  Overall
#64  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtableoss.oetiker.ch/­rrdtoolus.tmaxsoft.com/­products/­tibero
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsoss.oetiker.ch/­rrdtool/­doctechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleTobias OetikerTmaxSoft
Initial release2013201519992003
Current release4.1.0, June 20221.8.0, 20226, April 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPL V2 and FLOSScommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C infoImplementations in Java (e.g. RRD4J) and C# availableC and Assembler
Server operating systemsLinuxhostedHP-UX
Linux
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyes
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.nonono infoExporting into and restoring from XML files possibleyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
in-process shared library
Pipes
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
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-reducenonoPersistent Stored Procedure (PSM)
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyes
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.nonoyesno infoplanned for next version
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard (SQL 92, SQL 99)

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More resources
Apache ImpalaGoogle Cloud BigtableRRDtoolTibero
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