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DBMS > Axibase vs. CrateDB vs. Firebird vs. HugeGraph

System Properties Comparison Axibase vs. CrateDB vs. Firebird vs. HugeGraph

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Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonCrateDB  Xexclude from comparisonFirebird  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDistributed Database based on LuceneFirebird is an open source RDBMS forked from Borland's InterBaseA fast-speed and highly-scalable Graph DBMS
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score20.50
Rank#30  Overall
#18  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteaxibase.com/­docs/­atsd/­financecratedb.comwww.firebirdsql.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationcratedb.com/­docswww.firebirdsql.org/­en/­reference-manualshugegraph.apache.org/­docs
DeveloperAxibase CorporationCrateFirebird FoundationBaidu
Initial release201320132000 infoAs fork of Borland's InterBase2018
Current release155855.0.0, January 20240.9
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen SourceOpen Source infoInitial Developer's Public LicenseOpen 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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC and C++Java
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Linux
macOS
Unix
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyesyes
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 indexesnoyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilityyesno
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesGo
Java
PHP
Python
R
Ruby
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
Groovy
Java
Python
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)PSQLasynchronous Gremlin script jobs
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Foreign keys infoReferential integritynonoyesyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyes
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.noyes
User concepts infoAccess controlrights management via user accountsUsers with fine-grained authorization conceptUsers, roles and permissions
More information provided by the system vendor
AxibaseCrateDBFirebirdHugeGraph
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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AxibaseCrateDBFirebirdHugeGraph
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