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DBMS > AlaSQL vs. atoti vs. CrateDB vs. Google Cloud Spanner

System Properties Comparison AlaSQL vs. atoti vs. CrateDB vs. Google Cloud Spanner

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Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonatoti  Xexclude from comparisonCrateDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
DescriptionJavaScript DBMS libraryAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Distributed Database based on LuceneA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelDocument store
Relational DBMS
Object oriented DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Websitealasql.orgatoti.iocratedb.comcloud.google.com/­spanner
Technical documentationgithub.com/­AlaSQL/­alasqldocs.atoti.iocratedb.com/­docscloud.google.com/­spanner/­docs
DeveloperAndrey Gershun & Mathias R. WulffActiveViamCrateGoogle
Initial release201420132017
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercial infofree versions availableOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
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 languageJavaScriptJavaJava
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or datenoyesyes
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 indexesnoyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.Multidimensional Expressions (MDX)yes, but no triggers and constraints, and PostgreSQL compatibilityyes infoQuery statements complying to ANSI 2011
APIs and other access methodsJavaScript APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesJavaScript.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
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoPythonuser defined functions (Javascript)no
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneConfigurable replication on table/partition-levelMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlnorights management via user accountsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
AlaSQLatotiCrateDBGoogle Cloud Spanner
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
AlaSQLatotiCrateDBGoogle Cloud Spanner
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