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DBMS > Apache Drill vs. EsgynDB vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. TerarkDB

System Properties Comparison Apache Drill vs. EsgynDB vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used in-process key-value storeA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websitedrill.apache.orgwww.esgyn.cncloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­bytedance/­terarkdb
Technical documentationdrill.apache.org/­docscloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software FoundationEsgynGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleByteDance, originally Terark
Initial release20122015201519942016
Current release1.20.3, January 202318.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infocommercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinux
OS X
Windows
LinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnonono
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.nononoyes infoonly with the Berkeley DB XML editionno
Secondary indexesnoyesnoyesno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyesnoyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
C++ API
Java API
Supported programming languagesC++All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++
Java
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresnonono
Triggersnononoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenonoyesyes
User concepts infoAccess controlDepending on the underlying data sourcefine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Apache DrillEsgynDBGoogle Cloud BigtableOracle Berkeley DBTerarkDB
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