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DBMS > Apache Impala vs. Cloudflare Workers KV vs. EsgynDB vs. GBase

System Properties Comparison Apache Impala vs. Cloudflare Workers KV vs. EsgynDB vs. GBase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonEsgynDB  Xexclude from comparisonGBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational 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
Score0.39
Rank#274  Overall
#39  Key-value stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Websiteimpala.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvwww.esgyn.cnwww.gbase.cn
Technical documentationimpala.apache.org/­impala-docs.htmldevelopers.cloudflare.com/­kv/­api
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCloudflareEsgynGeneral Data Technology Co., Ltd.
Initial release2013201820152004
Current release4.1.0, June 2022GBase 8a, GBase 8s, GBase 8c
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaC, Java, Python
Server operating systemsLinuxhostedLinuxLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesStandard with numerous extensions
APIs and other access methodsJDBC
ODBC
HTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
ADO.NET
C API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava Stored Proceduresuser defined functions
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash) and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication between multi datacentersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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-standardyes

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More resources
Apache ImpalaCloudflare Workers KVEsgynDBGBase
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