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DBMS > EXASOL vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. Graphite vs. HugeGraph

System Properties Comparison EXASOL vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. Graphite vs. HugeGraph

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraphite  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeTime Series DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.47
Rank#76  Overall
#12  Document stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.exasol.comcloud.google.com/­bigtablecloud.google.com/­datastoregithub.com/­graphite-project/­graphite-webgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationwww.exasol.com/­resourcescloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsgraphite.readthedocs.iohugegraph.apache.org/­docs
DeveloperExasolGoogleGoogleChris DavisBaidu
Initial release20002015200820062018
Current release0.9
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonJava
Server operating systemshostedhostedLinux
Unix
Linux
macOS
Unix
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes, details hereNumeric data onlyyes
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 indexesyesnoyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLyesnoSQL-like query language (GQL)nono
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Sockets
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesJava
Lua
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript (Node.js)
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresuser defined functionsnousing Google App Enginenoasynchronous Gremlin script jobs
TriggersyesnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesyes infousing Google Cloud Dataflownovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.noneEventual Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infolockingyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers, roles and permissions

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More resources
EXASOLGoogle Cloud BigtableGoogle Cloud DatastoreGraphiteHugeGraph
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