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DBMS > CrateDB vs. Datastax Enterprise vs. FoundationDB vs. Hazelcast vs. YTsaurus

System Properties Comparison CrateDB vs. Datastax Enterprise vs. FoundationDB vs. Hazelcast vs. YTsaurus

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonFoundationDB  Xexclude from comparisonHazelcast  Xexclude from comparisonYTsaurus  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionDistributed Database based on LuceneDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Ordered key-value store. Core features are complimented by layers.A widely adopted in-memory data gridYTsaurus is an open source platform for distributed storage and processing.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Wide column storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeDocument store
Key-value store
Secondary database modelsRelational DBMSDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Document store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score5.93
Rank#56  Overall
#4  Wide column stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.21
Rank#324  Overall
#45  Document stores
#48  Key-value stores
Websitecratedb.comwww.datastax.com/­products/­datastax-enterprisegithub.com/­apple/­foundationdbhazelcast.comytsaurus.tech
Technical documentationcratedb.com/­docsdocs.datastax.comapple.github.io/­foundationdbhazelcast.org/­imdg/­docsytsaurus.tech/­docs/­en
DeveloperCrateDataStaxFoundationDBHazelcastYandex
Initial release20132011201320082023
Current release6.8, April 20206.2.28, November 20205.3.6, November 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
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.Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJavaC++JavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Linux
OS X
Windows
All OS with a Java VMUbuntu
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free infosome layers support schemasschema-free
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyesyes
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 strategyno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like DML and DDL statements (CQL); Spark SQLsupported in specific SQL layer onlySQL-like query languageYQL, an SQL-based language, is supported
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languages.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#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)noin SQL-layer onlyyes infoEvent Listeners, Executor Services
Triggersnoyesnoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"ShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelconfigurable replication factor, datacenter aware, advanced replication for edge computingyesyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Linearizable consistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynonoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyno infoAtomicity and isolation are supported for single operationsACIDone or two-phase-commit; repeatable reads; read commitedACID
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.noyesyes
User concepts infoAccess controlrights management via user accountsAccess rights for users can be defined per objectnoRole-based access controlAccess Control Lists
More information provided by the system vendor
CrateDBDatastax EnterpriseFoundationDBHazelcastYTsaurus
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Supporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Applications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Annual subscription
» more

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CrateDBDatastax EnterpriseFoundationDBHazelcastYTsaurus
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