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DBMS > Google Cloud Spanner vs. H2GIS vs. HugeGraph vs. Tarantool

System Properties Comparison Google Cloud Spanner vs. H2GIS vs. HugeGraph vs. Tarantool

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonH2GIS  Xexclude from comparisonHugeGraph  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA 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.Spatial extension of H2A fast-speed and highly-scalable Graph DBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSSpatial DBMSGraph DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsRelational DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.08
Rank#368  Overall
#7  Spatial DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitecloud.google.com/­spannerwww.h2gis.orggithub.com/­hugegraph
hugegraph.apache.org
www.tarantool.io
Technical documentationcloud.google.com/­spanner/­docswww.h2gis.org/­docs/­homehugegraph.apache.org/­docswww.tarantool.io/­en/­doc
DeveloperGoogleCNRSBaiduVK
Initial release2017201320182008
Current release0.92.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoLGPL 3.0Open Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemshostedLinux
macOS
Unix
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yesnoFull-featured ANSI SQL support
APIs and other access methodsgRPC (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
Open binary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
JavaGroovy
Java
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes infobased on H2asynchronous Gremlin script jobsLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes infobased on H2yes infodepending on used storage backend, e.g. Cassandra and HBaseAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on H2Users, roles and permissionsAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
Google Cloud SpannerH2GISHugeGraphTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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