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DBMS > Apache Impala vs. Apache Phoenix vs. Google Cloud Datastore vs. Hawkular Metrics vs. STSdb

System Properties Comparison Apache Impala vs. Apache Phoenix vs. Google Cloud Datastore vs. Hawkular Metrics vs. STSdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSRelational DBMSDocument storeTime Series DBMSKey-value store
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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orgphoenix.apache.orgcloud.google.com/­datastorewww.hawkular.orggithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmlphoenix.apache.orgcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationGoogleCommunity supported by Red HatSTS Soft SC
Initial release20132014200820142011
Current release4.1.0, June 20225.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaC#
Server operating systemsLinuxLinux
Unix
Windows
hostedLinux
OS X
Windows
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes infoprimitive types and user defined types (classes)
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.nononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsusing Google App Enginenono
TriggersnonoCallbacks using the Google Apps Engineyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Apache ImpalaApache PhoenixGoogle Cloud DatastoreHawkular MetricsSTSdb
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