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DBMS > HugeGraph vs. QuestDB vs. RocksDB vs. Tkrzw

System Properties Comparison HugeGraph vs. QuestDB vs. RocksDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonQuestDB  Xexclude from comparisonRocksDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSA high performance open source SQL database for time series dataEmbeddable persistent key-value store optimized for fast storage (flash and RAM)A 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 modelGraph DBMSTime Series DBMSKey-value storeKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
questdb.iorocksdb.orgdbmx.net/­tkrzw
Technical documentationhugegraph.apache.org/­docsquestdb.io/­docsgithub.com/­facebook/­rocksdb/­wiki
DeveloperBaiduQuestDB Technology IncFacebook, Inc.Mikio Hirabayashi
Initial release2018201420132020
Current release0.98.11.4, April 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustC++C++
Server operating systemsLinux
macOS
Unix
Linux
macOS
Windows
LinuxLinux
macOS
Data schemeyesyes infoschema-free via InfluxDB Line Protocolschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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 indexesyes infoalso supports composite index and range indexnono
SQL infoSupport of SQLnoSQL with time-series extensionsnono
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
C++ API
Java API
Supported programming languagesGroovy
Java
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C
C++
Go
Java
Perl
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning (by timestamps)horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication with eventual consistencyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesyes
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.yesyes infothrough memory mapped filesyesyes infousing specific database classes
User concepts infoAccess controlUsers, roles and permissionsnono
More information provided by the system vendor
HugeGraphQuestDBRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
HugeGraphQuestDBRocksDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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