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DBMS > Apache Phoenix vs. CrateDB vs. Microsoft Azure AI Search vs. Sadas Engine vs. Vertica

System Properties Comparison Apache Phoenix vs. CrateDB vs. Microsoft Azure AI Search vs. Sadas Engine vs. Vertica

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCrateDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Database based on LuceneSearch-as-a-service for web and mobile app developmentSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsCloud 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 DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Search engineRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSVector DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitephoenix.apache.orgcratedb.comazure.microsoft.com/­en-us/­services/­searchwww.sadasengine.comwww.vertica.com
Technical documentationphoenix.apache.orgcratedb.com/­docslearn.microsoft.com/­en-us/­azure/­searchwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationvertica.com/­documentation
DeveloperApache Software FoundationCrateMicrosoftSADAS s.r.l.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20142013201520062005
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V18.012.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial infofree trial version availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesnono 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 languageJavaJavaC++C++
Server operating systemsLinux
Unix
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedAIX
Linux
Windows
Linux
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yesyesYes, 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.nonononono
Secondary indexesyesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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#
Java
JavaScript
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functions (Javascript)nonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Configurable replication on table/partition-levelyes infoImplicit feature of the cloud servicenoneMulti-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 methodsHadoop integrationnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategynoACID
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.yesnonoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyrights management via user accountsyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache PhoenixCrateDBMicrosoft Azure AI SearchSadas EngineVertica 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
Apache PhoenixCrateDBMicrosoft Azure AI SearchSadas EngineVertica infoOpenText™ Vertica™
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