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DBMS > CockroachDB vs. Google Cloud Firestore vs. Hazelcast vs. Sphinx vs. Tkrzw

System Properties Comparison CockroachDB vs. Google Cloud Firestore vs. Hazelcast vs. Sphinx vs. Tkrzw

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSDocument storeKey-value storeSearch engineKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.cockroachlabs.comfirebase.google.com/­products/­firestorehazelcast.comsphinxsearch.comdbmx.net/­tkrzw
Technical documentationwww.cockroachlabs.com/­docsfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperCockroach LabsGoogleHazelcastSphinx Technologies Inc.Mikio Hirabayashi
Initial release20152017200820012020
Current release23.1.1, May 20235.3.6, November 20233.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++C++
Server operating systemsLinux
macOS
Windows
hostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemedynamic schemaschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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 indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes, wire compatible with PostgreSQLnoSQL-like query languageSQL-like query language (SphinxQL)no
APIs and other access methodsJDBCAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor Servicesnono
Triggersnoyes, with Cloud Functionsyes infoEventsnono
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 RAFTShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replicationyes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access controlnono

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CockroachDBGoogle Cloud FirestoreHazelcastSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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