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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Graph Engine vs. Infobright vs. OrigoDB

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Graph Engine vs. Infobright vs. OrigoDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonInfobright  Xexclude from comparisonOrigoDB  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendA fully ACID in-memory object graph database
Primary database modelRelational DBMSKey-value store
Wide column store
Graph DBMS
Key-value store
Relational DBMSDocument store
Object oriented DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score1.02
Rank#192  Overall
#90  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.graphengine.ioignitetech.com/­softwarelibrary/­infobrightdborigodb.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualorigodb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftIgnite Technologies Inc.; formerly InfoBright Inc.Robert Friberg et al
Initial release20132015201020052009 infounder the name LiveDB
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoMIT Licensecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CCC#
Server operating systemsLinuxhosted.NETLinux
Windows
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesUser defined using .NET types and collections
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.nonononono infocan be achieved using .NET
Secondary indexesyesnono infoKnowledge Grid Technology used insteadyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyesno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIADO.NET
JDBC
ODBC
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesnoyes
Triggersnonononoyes infoDomain Events
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningnonehorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-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)Immediate Consistency
Foreign keys infoReferential integritynonononodepending on model
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes infoWrite ahead log
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
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)fine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesRole based authorization

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More resources
Apache ImpalaGoogle Cloud BigtableGraph Engine infoformer name: TrinityInfobrightOrigoDB
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