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DBMS > Apache Impala vs. Brytlyt vs. etcd vs. Google Cloud Bigtable

System Properties Comparison Apache Impala vs. Brytlyt vs. etcd vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA distributed reliable key-value storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSRelational DBMSKey-value storeKey-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score7.05
Rank#53  Overall
#5  Key-value stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Websiteimpala.apache.orgbrytlyt.ioetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtable
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.ioetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytGoogle
Initial release201320162015
Current release4.1.0, June 20225.0, August 20233.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++ and CUDAGo
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
Windows infoexperimental
hosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnono
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnono
Triggersnoyesyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoAtomic single-row operations
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
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache ImpalaBrytlytetcdGoogle Cloud Bigtable
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