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DBMS > CockroachDB vs. Google Cloud Datastore vs. H2 vs. Solr

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. H2 vs. Solr

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2  Xexclude from comparisonSolr  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.cockroachlabs.comcloud.google.com/­datastorewww.h2database.comsolr.apache.org
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docswww.h2database.com/­html/­main.htmlsolr.apache.org/­resources.html
DeveloperCockroach LabsGoogleThomas MuellerApache Software Foundation
Initial release2015200820052006
Current release23.1.1, May 20232.2.220, July 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJava
Server operating systemsLinux
macOS
Windows
hostedAll OS with a Java VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedynamic schemaschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query language (GQL)yesSolr Parallel SQL Interface
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnousing Google App EngineJava Stored Procedures and User-Defined FunctionsJava plugins
TriggersnoCallbacks using the Google Apps Engineyesyes infoUser configurable commands triggered on index changes
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 RAFTShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using PaxosWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes

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CockroachDBGoogle Cloud DatastoreH2Solr
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