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DBMS > BigObject vs. Datomic vs. DuckDB vs. Google Cloud Spanner vs. HugeGraph

System Properties Comparison BigObject vs. Datomic vs. DuckDB vs. Google Cloud Spanner vs. HugeGraph

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatomic  Xexclude from comparisonDuckDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn embeddable, in-process, column-oriented SQL OLAP RDBMSA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitebigobject.iowww.datomic.comduckdb.orgcloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdocs.bigobject.iodocs.datomic.comduckdb.org/­docscloud.google.com/­spanner/­docshugegraph.apache.org/­docs
DeveloperBigObject, Inc.CognitectGoogleBaidu
Initial release20152012201820172018
Current release1.0.6735, June 20230.10, February 20240.9
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infolimited edition freeOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++Java
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMserver-lesshostedLinux
macOS
Unix
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononono
Secondary indexesyesyesyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
RESTful HTTP APIArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesClojure
Java
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresLuayes infoTransaction Functionsnonoasynchronous Gremlin script jobs
TriggersnoBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersnoneMulti-source replication with 3 replicas for regional instances.yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowvia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesnoyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions

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More resources
BigObjectDatomicDuckDBGoogle Cloud SpannerHugeGraph
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