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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonH2GIS  Xexclude from comparisonTarantool  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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 H2In-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSSpatial DBMSDocument store
Key-value store
Relational DBMS
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
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitecloud.google.com/­spannerwww.h2gis.orgwww.tarantool.iotrafodion.apache.org
Technical documentationcloud.google.com/­spanner/­docswww.h2gis.org/­docs/­homewww.tarantool.io/­en/­doctrafodion.apache.org/­documentation.html
DeveloperGoogleCNRSVKApache Software Foundation, originally developed by HP
Initial release2017201320082014
Current release2.10.0, May 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoLGPL 3.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++, Java
Server operating systemshostedBSD
Linux
macOS
Linux
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011yesFull-featured ANSI SQL supportyes
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
Open binary protocolADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
JavaC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes infobased on H2Lua, C and SQL stored proceduresJava Stored Procedures
Triggersnoyesyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes infobased on H2Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Immediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on H2Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerH2GISTarantoolTrafodion
DB-Engines blog posts

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

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