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DBMS > Coveo vs. CrateDB vs. Hazelcast vs. Sqrrl

System Properties Comparison Coveo vs. CrateDB vs. Hazelcast vs. Sqrrl

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonCrateDB  Xexclude from comparisonHazelcast  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDistributed Database based on LuceneA widely adopted in-memory data gridAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelSearch engineDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.14
Rank#116  Overall
#11  Search engines
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Websitewww.coveo.comcratedb.comhazelcast.comsqrrl.com
Technical documentationdocs.coveo.comcratedb.com/­docshazelcast.org/­imdg/­docs
DeveloperCoveoCrateHazelcastAmazon infooriginally Sqrrl Data, Inc.
Initial release2012201320082012
Current release5.8.1, August 20245.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query languageno
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
Java
JavaScript
Python
.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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infoEvent Listeners, Executor Servicesno
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelyes infoReplicated Mapselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno infounique row identifiers can be used for implementing an optimistic concurrency control strategyone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entity
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.noyes
User concepts infoAccess controlgranular access controls, API key management, content filtersrights management via user accountsRole-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
CoveoCrateDBHazelcastSqrrl
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