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DBMS > Apache Impala vs. Drizzle vs. Google Cloud Datastore vs. KairosDB vs. TerarkDB

System Properties Comparison Apache Impala vs. Drizzle vs. Google Cloud Datastore vs. KairosDB vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKairosDB  Xexclude from comparisonTerarkDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Time Series DBMS based on Cassandra or H2A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.67
Rank#233  Overall
#20  Time Series DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­datastoregithub.com/­kairosdb/­kairosdbgithub.com/­bytedance/­terarkdb
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docskairosdb.github.iobytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogleByteDance, originally Terark
Initial release20132008200820132016
Current release4.1.0, June 20227.2.4, September 20121.2.2, November 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infoApache 2.0commercial inforestricted open source version 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++C++JavaC++
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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 statementsyes infowith proprietary extensionsSQL-like query language (GQL)nono
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Graphite protocol
HTTP REST
Telnet API
C++ API
Java API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript infoNode.js
PHP
Python
C++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenousing Google App Enginenono
Triggersnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenono
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 MapReducenoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 integritynoyesyes 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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlno

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More resources
Apache ImpalaDrizzleGoogle Cloud DatastoreKairosDBTerarkDB
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