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DBMS > Drizzle vs. Impala vs. Microsoft Azure Cosmos DB vs. TimescaleDB

System Properties Comparison Drizzle vs. Impala vs. Microsoft Azure Cosmos DB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonImpala  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonTimescaleDB  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Analytic DBMS for HadoopGlobally distributed, horizontally scalable, multi-model database serviceA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument storeSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.71
Rank#38  Overall
#23  Relational DBMS
Score39.71
Rank#26  Overall
#3  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score4.38
Rank#81  Overall
#5  Time Series DBMS
Websitewww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlazure.microsoft.com/­services/­cosmos-dbwww.timescale.com
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmldocs.microsoft.com/­azure/­cosmos-dbdocs.timescale.com
DeveloperDrizzle project, originally started by Brian AkerClouderaMicrosoftTimescale
Initial release2008201320142017
Current release7.2.4, September 20123.4.0, April 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemsFreeBSD
Linux
OS X
LinuxhostedLinux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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
Secondary indexesyesyesyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCJDBC
ODBC
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceJavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno infohooks for callbacks inside the server can be used.noJavaScriptyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factoryes infoImplicit feature of the cloud serviceSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducewith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoMulti-item ACID transactions with snapshot isolation within a partitionACID
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.nono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard

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More resources
DrizzleImpalaMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBTimescaleDB
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