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DBMS > AgensGraph vs. Google Cloud Spanner vs. SiteWhere vs. Tarantool

System Properties Comparison AgensGraph vs. Google Cloud Spanner vs. SiteWhere vs. Tarantool

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSiteWhere  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLA 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.M2M integration platform for persisting/querying time series dataIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­spannergithub.com/­sitewhere/­sitewherewww.tarantool.io
Technical documentationbitnine.net/­documentationcloud.google.com/­spanner/­docssitewhere1.sitewhere.io/­index.htmlwww.tarantool.io/­en/­doc
DeveloperBitnine Global Inc.GoogleSiteWhereVK
Initial release2016201720102008
Current release2.1, December 20182.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC and C++
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
BSD
Linux
macOS
Data schemedepending on used data modelyespredefined schemeFlexible 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 indexesyesyesnoyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011noFull-featured ANSI SQL support
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP RESTOpen binary protocol
Supported programming languagesC
Java
JavaScript
Python
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnoLua, C and SQL stored procedures
Triggersnonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding infobased on 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 nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.selectable replication factor infobased on 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 methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptAccess 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
AgensGraphGoogle Cloud SpannerSiteWhereTarantool
DB-Engines blog posts

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

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