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DBMS > CockroachDB vs. Faircom EDGE vs. Google Cloud Spanner vs. Spark SQL vs. STSdb

System Properties Comparison CockroachDB vs. Faircom EDGE vs. Google Cloud Spanner vs. Spark SQL vs. STSdb

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA 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.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitewww.cockroachlabs.comwww.faircom.com/­products/­faircom-edgecloud.google.com/­spannerspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationwww.cockroachlabs.com/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­spanner/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCockroach LabsFairCom CorporationGoogleApache Software FoundationSTS Soft SC
Initial release20151979201720142011
Current release24.1.0, May 2024V3, October 20203.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercial infoRestricted, free version availablecommercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoANSI C, C++ScalaC#
Server operating systemsLinux
macOS
Windows
Android
Linux infoARM, x86
Raspbian
Windows
hostedLinux
OS X
Windows
Windows
Data schemedynamic schemaFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyesyes infoprimitive types and user defined types (classes)
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.noyesnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLyes, wire compatible with PostgreSQLyes infoANSI SQL queriesyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsno
APIs and other access methodsJDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
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
JDBC
ODBC
.NET Client API
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTFile partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication with 3 replicas for regional instances.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyes infowhen using SQLyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
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.noyesnono
User concepts infoAccess controlRole-based access controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
CockroachDBFaircom EDGE infoformerly c-treeEDGEGoogle Cloud SpannerSpark SQLSTSdb
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