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DBMS > CockroachDB vs. Google Cloud Datastore vs. QuestDB vs. Sphinx

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  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 PlatformA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeTime Series DBMSSearch engine
Secondary database modelsRelational 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
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.cockroachlabs.comcloud.google.com/­datastorequestdb.iosphinxsearch.com
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperCockroach LabsGoogleQuestDB Technology IncSphinx Technologies Inc.
Initial release2015200820142001
Current release23.1.1, May 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava (Zero-GC), C++, RustC++
Server operating systemsLinux
macOS
Windows
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemedynamic schemaschema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyes, details hereyesno
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query language (GQL)SQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
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 RAFTShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using PaxosSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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 Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infothrough memory mapped files
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
CockroachDBGoogle Cloud DatastoreQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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