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DBMS > CrateDB vs. EXASOL vs. Google Cloud Datastore

System Properties Comparison CrateDB vs. EXASOL vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitecratedb.comwww.exasol.comcloud.google.com/­datastore
Technical documentationcratedb.com/­docswww.exasol.com/­resourcescloud.google.com/­datastore/­docs
DeveloperCrateExasolGoogle
Initial release201320002008
License infoCommercial or Open SourceOpen Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
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 languageJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details here
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query language (GQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON 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
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsusing Google App Engine
TriggersnoyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor paths
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 strategyACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
CrateDBEXASOLGoogle Cloud Datastore
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
CrateDBEXASOLGoogle Cloud Datastore
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