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DBMS > Amazon Aurora vs. Apache Impala vs. CrateDB vs. Drizzle vs. Vertica

System Properties Comparison Amazon Aurora vs. Apache Impala vs. CrateDB vs. Drizzle vs. Vertica

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonCrateDB  Xexclude from comparisonDrizzle  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopDistributed Database based on LuceneMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument storeDocument storeRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcratedb.comwww.vertica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlcratedb.com/­docsvertica.com/­documentation
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaCrateDrizzle project, originally started by Brian AkerOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20152013201320082005
Current release4.1.0, June 20227.2.4, September 201212.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open SourceOpen Source infoGNU GPLcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageC++JavaC++C++
Server operating systemshostedLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
Linux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnonono
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functions (Javascript)noyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnonono infohooks for callbacks inside the server can be used.yes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon AuroraApache ImpalaCrateDBDrizzleVertica infoOpenText™ Vertica™
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
Amazon AuroraApache ImpalaCrateDBDrizzleVertica infoOpenText™ Vertica™
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