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DBMS > CockroachDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. QuestDB

System Properties Comparison CockroachDB vs. Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. QuestDB

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonQuestDB  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A Wide Column Store for rapid development using massive semi-structured datasetsA high performance open source SQL database for time series data
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeTime Series DBMS
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitewww.cockroachlabs.comcloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tablesquestdb.io
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­bigtable/­docsquestdb.io/­docs
DeveloperCockroach LabsGoogleMicrosoftQuestDB Technology Inc
Initial release2015201520122014
Current release24.1.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava (Zero-GC), C++, Rust
Server operating systemsLinux
macOS
Windows
hostedhostedLinux
macOS
Windows
Data schemedynamic schemaschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesnonono
SQL infoSupport of SQLyes, wire compatible with PostgreSQLnonoSQL with time-series extensions
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnononono
Triggersnononono
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 RAFTShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsoptimistic lockingACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes 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)Access rights based on private key authentication or shared access signatures
More information provided by the system vendor
CockroachDBGoogle Cloud BigtableMicrosoft Azure Table StorageQuestDB
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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More resources
CockroachDBGoogle Cloud BigtableMicrosoft Azure Table StorageQuestDB
Recent citations in the news

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